From 4c16542181bb1140c0784842a9918c23aa256df0 Mon Sep 17 00:00:00 2001 From: xiaying Date: Thu, 4 Jul 2024 11:53:45 +0800 Subject: [PATCH] MNN:Sync: Sync Internal 2.9.2 --- CMakeLists.txt | 13 +- docs/Makefile | 20 - docs/inference/module.md | 2 +- docs/tools/convert.md | 2 +- docs/transformers/diffusion.md | 44 +- include/MNN/MNNDefine.h | 2 +- project/android/updateTest.sh | 1 + pymnn/examples/MNNLlm/llm_example.py | 19 + pymnn/pip_package/MNN/llm/__init__.py | 76 + pymnn/pip_package/build_deps.py | 12 + pymnn/pip_package/setup.py | 9 + pymnn/src/MNN.cc | 22 +- pymnn/src/llm.h | 113 + pymnn/src/util.h | 10 +- pymnn/test/README.md | 4 +- source/backend/cpu/CPUAttention.cpp | 102 +- source/backend/cpu/CPUAttention.hpp | 5 +- source/backend/cpu/CPUBackend.cpp | 6 +- source/backend/cpu/CPUUnary.cpp | 1 + source/backend/metal/AllShader.cpp | 229 - source/backend/metal/AllShader.hpp | 1 - source/backend/metal/MetalBackend.hpp | 5 +- source/backend/metal/MetalBackend.mm | 576 +- source/backend/metal/ShaderMap.cpp | 1 - .../backend/metal/shader/MetalBackend.metal | 235 - .../backend/opencl/core/BufferConvertor.cpp | 4 +- source/backend/opencl/core/OpenCLGemmTune.cpp | 417 + .../backend/opencl/core/OpenCLOPRegister.cpp | 6 + .../opencl/core/OpenCLRunningUtils.cpp | 62 +- .../opencl/core/OpenCLRunningUtils.hpp | 3 +- .../opencl/core/runtime/OpenCLRuntime.cpp | 97 +- .../opencl/core/runtime/OpenCLRuntime.hpp | 8 +- .../buffer/AttentionBufExecution.cpp | 70 +- .../buffer/AttentionBufExecution.hpp | 9 +- .../execution/buffer/BinaryBufExecution.cpp | 2 +- .../execution/buffer/ConvBufExecution.cpp | 244 +- .../execution/buffer/ConvBufExecution.hpp | 6 +- .../buffer/ConvBufLowMemoryExecution.cpp | 427 +- .../buffer/ConvBufLowMemoryExecution.hpp | 6 +- .../execution/buffer/ConvBufWinograd.cpp | 284 +- .../execution/buffer/ConvBufWinograd.hpp | 5 + .../buffer/DepthwiseConvBufExecution.cpp | 5 +- .../buffer/GroupNormBufExecution.cpp | 267 + .../buffer/GroupNormBufExecution.hpp | 45 + .../execution/buffer/LoopBufExecution.cpp | 166 +- .../buffer/SelfAttentionBufExecution.cpp | 586 + .../buffer/SelfAttentionBufExecution.hpp | 79 + .../buffer/SplitGeluBufExecution.cpp | 103 + .../buffer/SplitGeluBufExecution.hpp | 39 + .../backend/opencl/execution/cl/argmax_buf.cl | 4 +- .../opencl/execution/cl/attention_buf.cl | 232 +- .../opencl/execution/cl/buffer_convert_buf.cl | 121 - .../execution/cl/buffer_convert_quant.cl | 242 + source/backend/opencl/execution/cl/conv_2d.cl | 288 +- .../opencl/execution/cl/conv_2d_int_buf.cl | 465 +- source/backend/opencl/execution/cl/gemm.cl | 100 +- .../execution/cl/gemm_quant_batch_buf.cl | 780 + .../opencl/execution/cl/gemv_conv1x1_buf.cl | 2239 +- .../opencl/execution/cl/groupnorm_buf.cl | 243 + .../opencl/execution/cl/layernorm_buf.cl | 20 +- .../backend/opencl/execution/cl/loop_buf.cl | 132 +- .../opencl/execution/cl/matmul_params_buf.cl | 743 +- .../opencl/execution/cl/opencl_codegen.py | 124 +- .../opencl/execution/cl/opencl_program.cc | 22863 +++++++++++++++- .../opencl/execution/cl/opencl_source_map.hpp | 341 + .../opencl/execution/cl/self_attention_buf.cl | 364 + .../opencl/execution/cl/splitgelu_buf.cl | 60 + .../execution/cl/winogradTransform_buf.cl | 262 +- .../opencl/execution/image/ConvExecution.cpp | 24 +- .../opencl/execution/image/ConvExecution.hpp | 4 +- .../image/ConvLowMemoryExecution.cpp | 152 +- .../execution/image/RasterExecution.cpp | 12 +- source/backend/opencl/schema/CLCache.fbs | 6 + .../opencl/schema/current/CLCache_generated.h | 144 +- source/core/Pipeline.cpp | 10 +- source/core/Tensor.cpp | 2 +- test/MNNTestSuite.cpp | 12 +- test/core/BackendTest.cpp | 2 +- tools/converter/source/onnx/IdentityOnnx.cpp | 18 + .../source/optimizer/merge/FuseFmhaV2.cpp | 247 + .../source/optimizer/merge/FuseGroupNorm.cpp | 44 +- .../source/optimizer/merge/FuseSplitGeLu.cpp | 37 +- .../onnxextra/ResolveIdentityOnnx.cpp | 56 - .../postconvert/MergeBNToConvolution.cpp | 19 +- .../postconvert/MergeScaleToConvolution.cpp | 20 +- .../postconvert/MergeToConvolution.hpp | 8 + .../postconvert/TransformGroupConvolution.cpp | 19 +- tools/cpp/ExprDebug.hpp | 4 +- tools/cpp/testModel.cpp | 1 + tools/cv/source/imgcodecs/imgcodecs.cpp | 2 +- tools/quantization/Helper.cpp | 47 +- tools/quantization/TensorStatistic.cpp | 74 +- tools/quantization/calibration.cpp | 1043 +- tools/quantization/calibration.hpp | 17 +- transformers/diffusion/README.md | 45 + transformers/diffusion/export/onnx_export.py | 212 + transformers/diffusion/main.cpp | 17 +- transformers/diffusion/pipeline.cpp | 117 +- transformers/diffusion/pipeline.hpp | 11 +- transformers/diffusion/scheduler/alphas.txt | 1000 + transformers/diffusion/tokenizer.cpp | 2 +- transformers/llm/engine/CMakeLists.txt | 18 +- transformers/llm/engine/include/llm.hpp | 61 +- transformers/llm/engine/include/tokenizer.hpp | 56 +- transformers/llm/engine/llm_demo.cpp | 1 + transformers/llm/engine/src/llm.cpp | 85 +- transformers/llm/engine/src/tokenizer.cpp | 30 +- transformers/llm/eval/evaluate_chat_ceval.py | 508 + 108 files changed, 33412 insertions(+), 4848 deletions(-) delete mode 100644 docs/Makefile create mode 100644 pymnn/examples/MNNLlm/llm_example.py create mode 100644 pymnn/pip_package/MNN/llm/__init__.py create mode 100644 pymnn/src/llm.h delete mode 100644 source/backend/metal/shader/MetalBackend.metal create mode 100644 source/backend/opencl/core/OpenCLGemmTune.cpp create mode 100644 source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp create mode 100644 source/backend/opencl/execution/buffer/GroupNormBufExecution.hpp create mode 100644 source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp create mode 100644 source/backend/opencl/execution/buffer/SelfAttentionBufExecution.hpp create mode 100644 source/backend/opencl/execution/buffer/SplitGeluBufExecution.cpp create mode 100644 source/backend/opencl/execution/buffer/SplitGeluBufExecution.hpp create mode 100644 source/backend/opencl/execution/cl/buffer_convert_quant.cl create mode 100644 source/backend/opencl/execution/cl/gemm_quant_batch_buf.cl create mode 100644 source/backend/opencl/execution/cl/groupnorm_buf.cl create mode 100644 source/backend/opencl/execution/cl/opencl_source_map.hpp create mode 100644 source/backend/opencl/execution/cl/self_attention_buf.cl create mode 100644 source/backend/opencl/execution/cl/splitgelu_buf.cl delete mode 100644 tools/converter/source/optimizer/onnxextra/ResolveIdentityOnnx.cpp create mode 100644 transformers/diffusion/README.md create mode 100644 transformers/diffusion/export/onnx_export.py create mode 100755 transformers/diffusion/scheduler/alphas.txt create mode 100644 transformers/llm/eval/evaluate_chat_ceval.py diff --git a/CMakeLists.txt b/CMakeLists.txt index bd2220bc7..abb66d6c8 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -636,11 +636,6 @@ IF(MNN_BUILD_CODEGEN) include(${CMAKE_CURRENT_LIST_DIR}/codegen/CMakeLists.txt) ENDIF() -IF(MNN_BUILD_LLM) - # add_definitions(-DMNN_BUILD_LLM) - include(${CMAKE_CURRENT_LIST_DIR}/transformers/llm/engine/CMakeLists.txt) -ENDIF() - # NPU IF(MNN_NPU) add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/source/backend/hiai/) @@ -735,6 +730,14 @@ IF(MNN_BUILD_OPENCV AND NOT MNN_SEP_BUILD) target_sources(MNN PRIVATE $) ENDIF() +IF(MNN_BUILD_LLM) + # add_definitions(-DMNN_BUILD_LLM) + include(${CMAKE_CURRENT_LIST_DIR}/transformers/llm/engine/CMakeLists.txt) + IF(NOT MNN_SEP_BUILD) + target_sources(MNN PRIVATE $) + ENDIF() +ENDIF() + if(CMAKE_SYSTEM_NAME MATCHES "^Linux") # Using -pthread, needed by thread-safe implemention of glibc, is better than only using -lpthread # https://stackoverflow.com/questions/23250863/difference-between-pthread-and-lpthread-while-compiling diff --git a/docs/Makefile b/docs/Makefile deleted file mode 100644 index d4bb2cbb9..000000000 --- a/docs/Makefile +++ /dev/null @@ -1,20 +0,0 @@ -# Minimal makefile for Sphinx documentation -# - -# You can set these variables from the command line, and also -# from the environment for the first two. -SPHINXOPTS ?= -SPHINXBUILD ?= sphinx-build -SOURCEDIR = . -BUILDDIR = _build - -# Put it first so that "make" without argument is like "make help". -help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -.PHONY: help Makefile - -# Catch-all target: route all unknown targets to Sphinx using the new -# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/inference/module.md b/docs/inference/module.md index d1bbd58e7..22347a576 100644 --- a/docs/inference/module.md +++ b/docs/inference/module.md @@ -225,7 +225,7 @@ MNN::TensorCallBackWithInfo callBack = [&](const std::vector& nten return true; }; -// 设置回调函数，需要是创建该 Module 时的 executor ，非多实例情况下用全局 executor 即可： +// 设置回调函数，需要时创建该 Module 时的 executor ，非多实例情况下用全局 executor 即可： Express::Executor::getGlobalExecutor()->setCallBack(std::move(beforeCallBack), std::move(callBack)); // forward would trigger callback diff --git a/docs/tools/convert.md b/docs/tools/convert.md index 98b1aac98..f8ab79101 100644 --- a/docs/tools/convert.md +++ b/docs/tools/convert.md @@ -48,7 +48,7 @@ Usage: --weightQuantAsymmetric 与weightQuantBits结合使用，决定是否用非对称量化，默认为`true` --compressionParamsFile arg - 使用MNN模型压缩工具箱生成的模型压缩信息文件 + 使用MNN模型压缩工具箱生成的模型压缩信息文件或根据用户提供的量化参数来生成对应的量化模型，量化参数文件可参考tools/converter/user_provide_quant_params.json --saveStaticModel 固定输入形状，保存静态模型， default: false diff --git a/docs/transformers/diffusion.md b/docs/transformers/diffusion.md index da22cb304..ffe6eb9d0 100644 --- a/docs/transformers/diffusion.md +++ b/docs/transformers/diffusion.md @@ -1,3 +1,45 @@ # 扩散模型 -TODO \ No newline at end of file +## 模型支持与下载 + +[Download-runwayml/stable-diffusion-v1-5]: +https://huggingface.co/runwayml/stable-diffusion-v1-5/tree/main +[Download-IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1]: +https://huggingface.co/IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1/tree/main + +## 模型转换 +### 将Huggingface的Stable Diffusion模型 转为onnx模型 +python export/onnx_export.py \ + --model_path hf_sd_load_path \ + --output_path onnx_save_path + +### 将onnx模型转为mnn模型 +新建diffusion mnn模型文件夹，将转好的mnn文件放在该文件夹下。 +./MNNConvert -f ONNX --modelFile onnx_save_path/text_encoder/model.onnx --MNNModel mnn_save_path/text_encoder.mnn --weightQuantBits 8 --bizCode biz +./MNNConvert -f ONNX --modelFile onnx_save_path/unet/model.onnx --MNNModel mnn_save_path/unet.mnn --transformerFuse --weightQuantBits 8 --bizCode biz +./MNNConvert -f ONNX --modelFile onnx_save_path/vae_decoder/model.onnx --keepInputFormat --MNNModel mnn_save_path/vae_decoder.mnn --weightQuantBits 8 --bizCode biz + +## 编译Diffusion Demo +### Linux/MAC/Windows上 +cmake .. -DMNN_BUILD_DIFFUSION=ON -DMNN_BUILD_OPENCV=ON -DMNN_IMGCODECS=ON -DMNN_OPENCL=ON -DMNN_SEP_BUILD=OFF -DMNN_SUPPORT_TRANSFORMER_FUSE=ON + +### Android上 +cd project/android/build +../build_64.sh -DMNN_BUILD_DIFFUSION=ON -DMNN_BUILD_OPENCV=ON -DMNN_IMGCODECS=ON -DMNN_OPENCL=ON -DMNN_SEP_BUILD=OFF -DMNN_SUPPORT_TRANSFORMER_FUSE=ON + +## 运行Diffusion Demo +./diffusion_demo +其中，resource_path 就是mnn模型文件的路径，除了mnn文件，还需要 +（1）将MNN目录transformers/diffusion/scheduler/alphas.txt文件拷贝到该文件夹下。 +（2）针对stable-diffusion-v1-5模型需要将huggingfacetokenizer目录下merges.txt和vocab.json拷贝到该文件夹中。针对Taiyi-Stable-Diffusion模型需要将huggingfacetokenizer目录下vocab.txt拷贝到该文件夹中。 + +model_type是目前支持的两种diffusion模型的类别。如果是stable-diffusion-v1-5模型设为0，如果是Taiyi-Stable-Diffusion模型设为1。 + +output_image_name是生成图片的名字，默认图片位置在当前运行目录下。 + +input_text是文生图的prompt，如果是stable-diffusion-v1-5模型建议英文prompt，如果是Taiyi-Stable-Diffusion建议中文prompt。 + +运行指令例如: +./diffusion_demo mnn_save_path 0 demo.jpg "a cute cat" +./diffusion_demo mnn_save_path 1 demo.jpg "一只可爱的猫" + diff --git a/include/MNN/MNNDefine.h b/include/MNN/MNNDefine.h index dc81a3872..b6d6645db 100644 --- a/include/MNN/MNNDefine.h +++ b/include/MNN/MNNDefine.h @@ -69,6 +69,6 @@ MNN_ERROR("Check failed: %s ==> %s\n", #success, #log); \ #define STR(x) STR_IMP(x) #define MNN_VERSION_MAJOR 2 #define MNN_VERSION_MINOR 9 -#define MNN_VERSION_PATCH 1 +#define MNN_VERSION_PATCH 2 #define MNN_VERSION STR(MNN_VERSION_MAJOR) "." STR(MNN_VERSION_MINOR) "." STR(MNN_VERSION_PATCH) #endif /* MNNDefine_h */ diff --git a/project/android/updateTest.sh b/project/android/updateTest.sh index 7d682bd5a..29c13242c 100755 --- a/project/android/updateTest.sh +++ b/project/android/updateTest.sh @@ -4,6 +4,7 @@ DIR=MNN make -j16 adb push ./libllm.so /data/local/tmp/MNN/libllm.so adb push ./llm_demo /data/local/tmp/MNN/llm_demo +adb push ./diffusion_demo /data/local/tmp/MNN/diffusion_demo adb push ./libMNN.so /data/local/tmp/$DIR/libMNN.so adb push ./libMNN_CL.so /data/local/tmp/$DIR/libMNN_CL.so adb push ./libMNN_Vulkan.so /data/local/tmp/$DIR/libMNN_Vulkan.so diff --git a/pymnn/examples/MNNLlm/llm_example.py b/pymnn/examples/MNNLlm/llm_example.py new file mode 100644 index 000000000..ec96c0afb --- /dev/null +++ b/pymnn/examples/MNNLlm/llm_example.py @@ -0,0 +1,19 @@ +import MNN.llm as llm +import sys + +if len(sys.argv) < 2: + print('usage: python llm_example.py ') + exit(1) + +config_path = sys.argv[1] +# create model +qwen = llm.create(config_path) +# load model +qwen.load() + +# response stream +out = qwen.response('你好', True) +print(out) + +out_ids = qwen.generate([151644, 872, 198, 108386, 151645, 198, 151644, 77091]) +print(out_ids) diff --git a/pymnn/pip_package/MNN/llm/__init__.py b/pymnn/pip_package/MNN/llm/__init__.py new file mode 100644 index 000000000..f144b3e06 --- /dev/null +++ b/pymnn/pip_package/MNN/llm/__init__.py @@ -0,0 +1,76 @@ +import _mnncengine.llm as _F + +class LLM(_F.LLM): + def load(self, model_dir): + ''' + load model from model_dir + + Parameters + ---------- + model_dir : model path (split) or model name (single) + + Returns + ------- + None + + Example: + ------- + >>> llm.load('../qwen-1.8b-in4/conig.json') + ''' + super.load(model_dir) + + def generate(self, input_ids): + ''' + generate by input_ids + + Parameters + ---------- + input_ids : input token ids, list of int + + Returns + ------- + output_ids : output token ids, list of int + + Example: + ------- + >>> input_ids = [151644, 872, 198, 108386, 151645, 198, 151644, 77091] + >>> output_ids = qwen.generate(input_ids) + ''' + return super.generate(input_ids) + + def response(self, prompt, stream = False): + ''' + response by prompt + + Parameters + ---------- + prompt : input prompt + stream : generate string stream, default is False + + Returns + ------- + res : output string + + Example: + ------- + >>> res = qwen.response('Hello', True) + ''' + return super.response(prompt, stream) + +def create(config_path): + ''' + create LLM instance by `config.json` + + Parameters + ---------- + config_path : config path or model path + + Returns + ------- + llm : LLM instance + + Example: + ------- + >>> qwen = llm.create('./qwen-1.8b-int4/config.json') + ''' + return _F.create(config_path) \ No newline at end of file diff --git a/pymnn/pip_package/build_deps.py b/pymnn/pip_package/build_deps.py index 30be4a31a..8d0297c90 100644 --- a/pymnn/pip_package/build_deps.py +++ b/pymnn/pip_package/build_deps.py @@ -29,6 +29,8 @@ USE_RENDER = False USE_SSE = True USE_OPENMP = False +USE_LLM = False +USE_ARM82 = False if len(sys.argv) > 1 and sys.argv[1] != None: if "trt" in sys.argv[1]: @@ -51,6 +53,10 @@ USE_SSE = False if "openmp" in sys.argv[1]: USE_OPENMP = True + if "llm" in sys.argv[1]: + USE_LLM = True + if "arm82" in sys.argv[1]: + USE_ARM82 = True print ("USE_INTERNAL:", USE_INTERNAL) print ("USE_TRT:", USE_TRT) @@ -62,6 +68,8 @@ print ("USE_RENDER:", USE_RENDER) print ("USE_SSE:", USE_SSE) print ("USE_OPENMP:", USE_OPENMP) +print ("USE_LLM:", USE_LLM) +print ("USE_ARM82:", USE_ARM82) def build_deps(): """ build depency """ @@ -79,6 +87,10 @@ def build_deps(): extra_opts += ' -DMNN_VULKAN=ON -DMNN_VULKAN_IMAGE=OFF' if USE_OPENCL: extra_opts += ' -DMNN_OPENCL=ON' + if USE_LLM: + extra_opts += ' -DMNN_BUILD_LLM=ON -DMNN_LOW_MEMORY=ON -DMNN_SUPPORT_TRANSFORMER_FUSE=ON' + if USE_ARM82: + extra_opts += ' -DMNN_ARM82=ON' extra_opts += ' -DMNN_USE_THREAD_POOL=OFF -DMNN_OPENMP=ON' if USE_OPENMP else ' -DMNN_USE_THREAD_POOL=ON -DMNN_OPENMP=OFF' if IS_WINDOWS: diff --git a/pymnn/pip_package/setup.py b/pymnn/pip_package/setup.py index 6651a76ee..633968edb 100644 --- a/pymnn/pip_package/setup.py +++ b/pymnn/pip_package/setup.py @@ -214,6 +214,9 @@ def configure_extension_build(): engine_include_dirs += [os.path.join(root_dir, "3rd_party", "rapidjson")] # cv include engine_include_dirs += [os.path.join(root_dir, "tools", "cv", "include")] + # llm include + engine_include_dirs += [os.path.join(root_dir, "transformers", "llm", "engine", "include")] + engine_include_dirs += [os.path.join(root_dir, "3rd_party")] engine_include_dirs += [np.get_include()] lib_files = [] @@ -247,6 +250,12 @@ def configure_extension_build(): # add libTorch dependency torch_lib = None cmakecache = os.path.join(root_dir, BUILD_DIR, 'CMakeCache.txt') + # llm + for line in open(cmakecache, 'rt').readlines(): + if 'MNN_BUILD_LLM' in line: + if 'ON' in line: + extra_compile_args += ['-DPYMNN_LLM_API'] + # torch lib for line in open(cmakecache, 'rt').readlines(): if 'TORCH_LIBRARY' in line: torch_lib = os.path.dirname(line[line.find('=')+1:]) diff --git a/pymnn/src/MNN.cc b/pymnn/src/MNN.cc index f7d8dbaf1..1ec9a15e1 100644 --- a/pymnn/src/MNN.cc +++ b/pymnn/src/MNN.cc @@ -66,6 +66,10 @@ using RegularizationMethod = ParameterOptimizer::RegularizationMethod; #endif #endif +#ifdef PYMNN_LLM_API +#include "llm.h" +#endif + #ifdef PYMNN_INTERNAL_SERVING #include #include "internal/monitor_service.h" @@ -1610,7 +1614,7 @@ static PyObject* PyMNNTensor_fromNumpy(PyMNNTensor *self, PyObject *args) { return NULL; } DType dtype = htype2dtype(self->tensor->getType()); - int npy_type = PyArray_TYPE(data); + int npy_type = PyArray_TYPE((const PyArrayObject*)data); int itemsize = getitemsize(dtype, npy_type); PyArrayObject *data_cont= PyArray_GETCONTIGUOUS((PyArrayObject*)data); auto tmpBuffer = PyArray_DATA(data_cont); @@ -1946,7 +1950,7 @@ static PyObject* PyMNNCVImageProcess_convert(PyMNNCVImageProcess *self, PyObject #ifdef PYMNN_NUMPY_USABLE else if(gNumpyValid && PyArray_Check(source)) { // Array Data - int npy_type = PyArray_TYPE(source); + int npy_type = PyArray_TYPE((const PyArrayObject*)source); if(npy_type != NPY_UINT8) { PyErr_SetString(PyExc_Exception, "PyMNNCVImageProcess_convert: only numpy.uint8 is supported for numpy"); @@ -2710,6 +2714,20 @@ PyMODINIT_FUNC MOD_INIT_FUNC(void) { } #endif #endif +#ifdef PYMNN_LLM_API + // llm submodule + auto llm_module = def_submodule(m, "llm"); + if (PyType_Ready(&PyMNNLLM) < 0) { + PyErr_SetString(PyExc_Exception, "initMNN.llm: PyType_Ready PyMNNLLM failed"); + ERROR_RETURN + } + PyModule_AddObject(llm_module, "LLM", (PyObject *)PyType_FindTLSType(&PyMNNLLM)); + // add methods of llm + constexpr int llm_method_num = sizeof(PyMNNLLM_static_methods) / sizeof(PyMethodDef); + for (int i = 0; i < llm_method_num; i++) { + def_method(llm_module, &PyMNNLLM_static_methods[i]); + } +#endif #if PY_MAJOR_VERSION >= 3 return m; diff --git a/pymnn/src/llm.h b/pymnn/src/llm.h new file mode 100644 index 000000000..8e9fffcfd --- /dev/null +++ b/pymnn/src/llm.h @@ -0,0 +1,113 @@ +#include "llm.hpp" + +typedef struct { + PyObject_HEAD + Llm* llm; +} LLM; + +static PyObject* PyMNNLLM_new(struct _typeobject *type, PyObject *args, PyObject *kwds) { + LLM* self = (LLM *)type->tp_alloc(type, 0); + return (PyObject*)self; +} + +static PyObject* Py_str(PyObject *self) { + LLM* llm = (LLM*)self; + if (!llm) { + Py_RETURN_NONE; + } + return toPyObj("llm"); +} + +static PyObject* PyMNNLLM_load(LLM *self, PyObject *args) { + self->llm->load(); + Py_RETURN_NONE; +} + +static PyObject* PyMNNLLM_generate(LLM *self, PyObject *args) { + PyObject *input_ids = nullptr; + if (!PyArg_ParseTuple(args, "O", &input_ids) && isInts(input_ids)) { + Py_RETURN_NONE; + } + auto output_ids = self->llm->generate(toInts(input_ids)); + return toPyObj(output_ids); +} + +static PyObject* PyMNNLLM_response(LLM *self, PyObject *args) { + const char* query = NULL; + int stream = 0; + if (!PyArg_ParseTuple(args, "s|p", &query, &stream)) { + Py_RETURN_NONE; + } + LlmStreamBuffer buffer(nullptr); + std::ostream null_os(&buffer); + auto res = self->llm->response(query, stream ? &std::cout : &null_os); + return string2Object(res); +} + +static PyMethodDef PyMNNLLM_methods[] = { + {"load", (PyCFunction)PyMNNLLM_load, METH_VARARGS, "load model."}, + {"generate", (PyCFunction)PyMNNLLM_generate, METH_VARARGS, "generate `output_ids` by `input_ids`."}, + {"response", (PyCFunction)PyMNNLLM_response, METH_VARARGS, "response `query` without hsitory."}, + {NULL} /* Sentinel */ +}; + +static PyTypeObject PyMNNLLM = { + PyVarObject_HEAD_INIT(NULL, 0) + "LLM", /*tp_name*/ + sizeof(LLM), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + 0, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + 0, /*tp_compare*/ + Py_str, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash */ + 0, /*tp_call*/ + Py_str, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "LLM is mnn-llm's `Llm` python wrapper", /* tp_doc */ + 0, /* tp_traverse */ + 0, /* tp_clear */ + 0, /* tp_richcompare */ + 0, /* tp_weaklistoffset */ + 0, /* tp_iter */ + 0, /* tp_iternext */ + PyMNNLLM_methods, /* tp_methods */ + 0, /* tp_members */ + 0, /* tp_getset */ + 0, /* tp_base */ + 0, /* tp_dict */ + 0, /* tp_descr_get */ + 0, /* tp_descr_set */ + 0, /* tp_dictoffset */ + 0, /* tp_init */ + 0, /* tp_alloc */ + PyMNNLLM_new, /* tp_new */ +}; + +static PyObject* PyMNNLLM_create(PyObject *self, PyObject *args) { + if (!PyTuple_Size(args)) { + return NULL; + } + const char* path = NULL; + if (!PyArg_ParseTuple(args, "s", &path)) { + return NULL; + } + LLM *llm = (LLM *)PyObject_Call((PyObject*)&PyMNNLLM, PyTuple_New(0), NULL); + if (!llm) { + return NULL; + } + llm->llm = Llm::createLLM(path); + return (PyObject*)llm; +} + +static PyMethodDef PyMNNLLM_static_methods[] = { + {"create", PyMNNLLM_create, METH_VARARGS} +}; \ No newline at end of file diff --git a/pymnn/src/util.h b/pymnn/src/util.h index bd33cc895..4ed57f8ab 100644 --- a/pymnn/src/util.h +++ b/pymnn/src/util.h @@ -222,10 +222,10 @@ DType htype2dtype(halide_type_t type) { } if (type.code == halide_type_int && type.bits == 64) { return DType_INT64; - } + } if (type.code == halide_type_handle) { - return DType_STRING; - } + return DType_STRING; + } return DType_FLOAT; } #define CONVERT(src, dst, f)\ @@ -454,7 +454,7 @@ static vector toVec(PyObject* obj) { if (total_length == 0) { return values; } - int item_size = getnpysize(PyArray_TYPE(obj)); + int item_size = getnpysize(PyArray_TYPE((const PyArrayObject*)obj)); PyArrayObject *obj_cont= PyArray_GETCONTIGUOUS((PyArrayObject*)obj); auto tmpBuffer = PyArray_DATA(obj_cont); if(NULL == tmpBuffer) { @@ -518,7 +518,7 @@ static void* toPtr(PyObject *obj, DType dtype, int64_t& total_length, void* data PyMNN_ERROR_LOG("data size does not match each other"); return data; } - int npy_type = PyArray_TYPE(obj); + int npy_type = PyArray_TYPE((const PyArrayObject*)obj); int itemsize = getitemsize(dtype, npy_type); PyArrayObject *obj_cont= PyArray_GETCONTIGUOUS((PyArrayObject*)obj); auto tmpBuffer = PyArray_DATA(obj_cont); diff --git a/pymnn/test/README.md b/pymnn/test/README.md index 08b4a2d29..20be1dbf2 100644 --- a/pymnn/test/README.md +++ b/pymnn/test/README.md @@ -29,10 +29,10 @@ pip install prettytable python3 benchmark.py ``` -# 6. Playgroud Test (just internal usage) +# 6. Playgroud Test (just internal usage) ```bash # 拷贝AliNNModel所有模型和测试数据到MNN工作台工程下 python scripts/pullTestModel.py --alinnmodel_path ../../../AliNNModel --playground_path playground/playground # 拷贝AliNNModel指定模型（mobilenet, Ranfa）和测试数据到MNN工作台工程下 python scripts/pullTestModel.py --alinnmodel_path ../../../AliNNModel --playground_path playground/playground --models mobilenet Ranfa -``` +``` \ No newline at end of file diff --git a/source/backend/cpu/CPUAttention.cpp b/source/backend/cpu/CPUAttention.cpp index c37d9a3f7..a71472d1f 100644 --- a/source/backend/cpu/CPUAttention.cpp +++ b/source/backend/cpu/CPUAttention.cpp @@ -24,13 +24,16 @@ #define FLOAT16_T float #endif +// reduce the value of 'query' to 'query * FP16_QSCALE', avoid fp16 overflow +#define FP16_QSCALE 0.5 + namespace MNN { template static void prefill_pack(Tensor* query, Tensor* key, Tensor* value, char* query_ptr, char* key_ptr, char* value_ptr, int mMaxLength, int mNumHead, int mKvNumHead, int mHeadDim, int mValueH, - int eP, int hP, int query_e, int key_h, int seq_len, int h, int kv_h) { + int eP, int hP, int query_e, int key_h, int seq_len, int h, int kv_h, float q_scale) { auto query_src = query->host(); auto key_src = key->host(); auto value_src = value->host(); @@ -43,7 +46,7 @@ static void prefill_pack(Tensor* query, Tensor* key, Tensor* value, char* query_ for (int k = 0; k < eP; k++) { int s = i * eP + k; if (s < seq_len) { - query_dst[i * mHeadDim * eP + j * eP + k] = query_src[s * mNumHead * mHeadDim + h * mHeadDim + j]; + query_dst[i * mHeadDim * eP + j * eP + k] = query_src[s * mNumHead * mHeadDim + h * mHeadDim + j] * q_scale; } } } @@ -74,7 +77,7 @@ static void prefill_pack(Tensor* query, Tensor* key, Tensor* value, char* query_ template static void decode_pack(Tensor* query, Tensor* key, Tensor* value, char* query_ptr, char* key_ptr, char* value_ptr, - int mMaxLength, int mPastLength, int mHeadDim, int mValueH, int eP, int hP, int h, int kv_h) { + int mMaxLength, int mPastLength, int mHeadDim, int mValueH, int eP, int hP, int h, int kv_h, float q_scale) { auto query_src = query->host(); auto key_src = key->host(); auto value_src = value->host(); @@ -82,7 +85,7 @@ static void decode_pack(Tensor* query, Tensor* key, Tensor* value, char* query_p auto key_dst = reinterpret_cast(key_ptr); auto value_dst = reinterpret_cast(value_ptr); for (int i = 0; i < mHeadDim; i++) { - query_dst[i * eP] = query_src[h * mHeadDim + i]; + query_dst[i * eP] = query_src[h * mHeadDim + i] * q_scale; } // transpose key: [1, num_head, head_dim] -> numhead, [kv_seq_len/hP, head_dim, hP] int outside_offset = UP_DIV(mPastLength, hP); @@ -164,10 +167,10 @@ static void decode_softmax(float* mask_qk, float* softmax_qk, char* unpack_qk, c } void CPUAttention::allocKVCache() { - if (!mKVCache || mResource->mPastLength < mResource->mMaxLength) { + if (!mKVCache) { return; } - mResource->mMaxLength = mResource->mPastLength + mResource->mExpandChunk; + mResource->mMaxLength = ROUND_UP(mResource->mPastLength, mResource->mExpandChunk); // past_key: [1, numhead, headdim, maxlen] -> numhead, [headdim, maxlen] -> pack_b -> numhead, [maxlen/hP, head_dim, hP] mResource->mPastKey.reset(Tensor::createDevice({mResource->mKvNumHead, UP_DIV(mResource->mMaxLength, hP), mResource->mHeadDim, hP})); // past_value: [1, numhead, maxlen, headdim] -> numhead, [maxlen, headdim] -> pack_b -> numhead, [head_dim/hP, max_len, hP] @@ -202,66 +205,32 @@ void CPUAttention::reallocKVCache() { } mResource->mPastKey.reset(new_key); mResource->mPastValue.reset(new_value); - mTempQK.reset(Tensor::createDevice({mThreadNum, eP + 2, mResource->mMaxLength})); - backend()->onAcquireBuffer(mTempQK.get(), Backend::STATIC); } ErrorCode CPUAttention::onResize(const std::vector& inputs, const std::vector& outputs) { auto core = static_cast(backend())->functions(); - int unit = core->pack; - bytes = core->bytes; core->MNNGetMatMulPackMode(&eP, &lP, &hP); - + unit = core->pack; + bytes = core->bytes; auto query = inputs[0]; - auto key = inputs[1]; - auto value = inputs[2]; - auto mask = inputs[3]; auto shape = query->shape(); int seq_len = shape[1]; mThreadNum = ((CPUBackend *)backend())->threadNumber(); - mIsDecode = seq_len == 1; - if (mResource->mPastLength == 0 || seq_len > 1) { - mResource->mPastLength = seq_len; - } - mResource->mNumHead = shape[2]; - mResource->mKvNumHead = key->shape()[2]; mResource->mHeadDim = shape[3]; - mResource->mScale = 1.0 / sqrt(mResource->mHeadDim); - mResource->mValueH = UP_DIV(mResource->mHeadDim, hP); int query_e = UP_DIV(seq_len, eP); - int key_h = UP_DIV(seq_len, hP); - // mPastLength = 10; - // alloc kv cache - allocKVCache(); - - int tileCount = UP_DIV(mResource->mNumHead, mThreadNum); - - // temp_query mPackQ.reset(Tensor::createDevice({mThreadNum, query_e, mResource->mHeadDim, eP})); mPackQKV.reset(Tensor::createDevice({mThreadNum, UP_DIV(mResource->mHeadDim, unit), seq_len, unit})); - if (mIsDecode) { - mTempQK.reset(Tensor::createDevice({mThreadNum, eP + 2, mResource->mMaxLength})); - backend()->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC); - } else { - mTempQK.reset(Tensor::createDevice({mThreadNum, 4, seq_len, seq_len})); - backend()->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC); - } backend()->onAcquireBuffer(mPackQ.get(), Backend::DYNAMIC); backend()->onAcquireBuffer(mPackQKV.get(), Backend::DYNAMIC); backend()->onReleaseBuffer(mPackQ.get(), Backend::DYNAMIC); - backend()->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC); backend()->onReleaseBuffer(mPackQKV.get(), Backend::DYNAMIC); return NO_ERROR; } ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std::vector& outputs) { auto core = static_cast(backend())->functions(); - int unit = core->pack; - bytes = core->bytes; - core->MNNGetMatMulPackMode(&eP, &lP, &hP); auto matmulUnit = core->MNNPackedMatMul; auto matmulRemain = core->MNNPackedMatMulRemain; - auto query = inputs[0]; auto key = inputs[1]; auto value = inputs[2]; @@ -271,23 +240,34 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: int seq_len = shape[1]; mThreadNum = ((CPUBackend *)backend())->threadNumber(); mIsDecode = seq_len == 1; - if (mResource->mPastLength == 0 || seq_len > 1) { - mResource->mPastLength = seq_len; - } mResource->mNumHead = shape[2]; mResource->mKvNumHead = key->shape()[2]; int group_size = mResource->mNumHead / mResource->mKvNumHead; mResource->mHeadDim = shape[3]; mResource->mScale = 1.0 / sqrt(mResource->mHeadDim); + // reduce the value of 'query' to avoid fp16 overflow + float q_scale = 1.0; + if (bytes == 2) { + q_scale = FP16_QSCALE; + mResource->mScale /= q_scale; + } mResource->mValueH = UP_DIV(mResource->mHeadDim, hP); int query_e = UP_DIV(seq_len, eP); int key_h = UP_DIV(seq_len, hP); - // mPastLength = 10; - int tileCount = UP_DIV(mResource->mNumHead, mThreadNum); - // try calloc kv cache - mPrefill = [=](int tId){ + std::shared_ptr mTempQK; + if (mIsDecode) { + reallocKVCache(); + mTempQK.reset(Tensor::createDevice({mThreadNum, eP + 2, mResource->mPastLength + 1})); + } else { + mResource->mPastLength = seq_len; + allocKVCache(); + mTempQK.reset(Tensor::createDevice({mThreadNum, 4, seq_len, seq_len})); + } + backend()->onAcquireBuffer(mTempQK.get(), Backend::STATIC); + + std::function mPrefill = [=](int tId){ auto pack_q = mPackQ->host() + tId * query_e * mResource->mHeadDim * eP * bytes; auto pack_qk = mTempQK->host() + tId * 4 * seq_len * seq_len * bytes; auto unpack_qk = pack_qk + seq_len * seq_len * 2 * bytes; @@ -302,9 +282,9 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: auto key_dst = mResource->mPastKey->host() + kv_h * UP_DIV(mResource->mMaxLength, hP) * mResource->mHeadDim * hP * bytes; auto value_dst = mResource->mPastValue->host() + kv_h * mResource->mValueH * mResource->mMaxLength * hP * bytes; if (bytes == 2) { - prefill_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mNumHead, mResource->mKvNumHead, mResource->mHeadDim, mResource->mValueH, eP, hP, query_e, key_h, seq_len, h, kv_h); + prefill_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mNumHead, mResource->mKvNumHead, mResource->mHeadDim, mResource->mValueH, eP, hP, query_e, key_h, seq_len, h, kv_h, q_scale); } else { - prefill_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mNumHead, mResource->mKvNumHead, mResource->mHeadDim, mResource->mValueH, eP, hP, query_e, key_h, seq_len, h, kv_h); + prefill_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mNumHead, mResource->mKvNumHead, mResource->mHeadDim, mResource->mValueH, eP, hP, query_e, key_h, seq_len, h, kv_h, q_scale); } // query @ key int loop_e = seq_len / eP; @@ -331,7 +311,7 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: parameters[5] = 0; matmulRemain((float*)(pack_qk + (loop_e * eP * unit) * bytes), (float*)(pack_q + (loop_e * mResource->mHeadDim * eP) * bytes), (float*)key_dst, remain, parameters, nullptr, nullptr, nullptr, nullptr); } - int area_offset[1] {seq_len}; + int area_offset[2] {seq_len, 0}; core->MNNUnpackCUnitTranspose((float*)unpack_qk, (float*)pack_qk, seq_len, seq_len, area_offset); // div scale and mask auto mask_ptr = mask->host(); @@ -373,7 +353,7 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: } }; - mDecode = [=](int tId) { + std::function mDecode = [=](int tId) { int kv_seq_len = mResource->mPastLength + 1; auto pack_q = mPackQ->host() + tId * mResource->mHeadDim * eP * bytes; auto pack_qk = mTempQK->host() + tId * (eP + 2) * kv_seq_len * bytes; @@ -389,9 +369,9 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: auto value_dst = mResource->mPastValue->host() + kv_h * mResource->mValueH * mResource->mMaxLength * hP * bytes; // pack for matmul if (bytes == 2) { - decode_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mPastLength, mResource->mHeadDim, mResource->mValueH, eP, hP, h, kv_h); + decode_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mPastLength, mResource->mHeadDim, mResource->mValueH, eP, hP, h, kv_h, q_scale); } else { - decode_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mPastLength, mResource->mHeadDim, mResource->mValueH, eP, hP, h, kv_h); + decode_pack(query, key, value, pack_q, key_dst, value_dst, mResource->mMaxLength, mResource->mPastLength, mResource->mHeadDim, mResource->mValueH, eP, hP, h, kv_h, q_scale); } // query @ key: [1, head_dim] @ [head_dim, kv_seq_len] -> [1, kv_seq_len] size_t shapeParameters[6]; @@ -403,7 +383,7 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: parameters[4] = 0; parameters[5] = 0; matmulRemain((float*)pack_qk, (float*)pack_q, (float*)key_dst, seq_len, parameters, nullptr, nullptr, nullptr, nullptr); - int area_offset[1] {seq_len}; + int area_offset[2] {seq_len, 0}; core->MNNUnpackCUnitTranspose((float*)unpack_qk, (float*)pack_qk, seq_len, kv_seq_len, area_offset); if (bytes == 2) { decode_softmax(mask_qk, softmax_qk, unpack_qk, pack_qk, mResource->mScale, eP, kv_seq_len); @@ -426,14 +406,16 @@ ErrorCode CPUAttention::onExecute(const std::vector& inputs, const std: core->MNNUnpackCUnitTranspose((float*)dst_ptr, (float*)pack_qkv, 1, mResource->mHeadDim, area_offset); } }; - mFunction = mIsDecode ? mDecode : mPrefill; - reallocKVCache(); - // compute + + std::function mFunction = mIsDecode ? mDecode : mPrefill; MNN_CONCURRENCY_BEGIN(tId, mThreadNum) { mFunction((int)tId); } MNN_CONCURRENCY_END(); - mResource->mPastLength += mIsDecode; + if(mIsDecode) { + mResource->mPastLength++; + } + backend()->onReleaseBuffer(mTempQK.get(), Backend::STATIC); return NO_ERROR; } diff --git a/source/backend/cpu/CPUAttention.hpp b/source/backend/cpu/CPUAttention.hpp index 6e3154db7..bc48de6b4 100644 --- a/source/backend/cpu/CPUAttention.hpp +++ b/source/backend/cpu/CPUAttention.hpp @@ -39,9 +39,8 @@ class CPUAttention : public Execution { bool mKVCache; int mThreadNum = 1; std::shared_ptr mResource; - std::shared_ptr mTempQK, mPackQ, mPackQKV; - int eP, lP, hP, bytes; - std::function mFunction, mPrefill, mDecode; + std::shared_ptr mPackQ, mPackQKV; + int eP, lP, hP, bytes, unit; }; } // namespace MNN diff --git a/source/backend/cpu/CPUBackend.cpp b/source/backend/cpu/CPUBackend.cpp index 0a9637377..66c349c37 100644 --- a/source/backend/cpu/CPUBackend.cpp +++ b/source/backend/cpu/CPUBackend.cpp @@ -481,7 +481,11 @@ void CPUBackend::onCopyBuffer(const Tensor* srcTensor, const Tensor* dstTensor) auto& srcBuffer = srcTensor->buffer(); auto& dstBuffer = dstTensor->buffer(); - MNN_ASSERT(srcBuffer.dimensions == dstBuffer.dimensions); + if (srcBuffer.dimensions != dstBuffer.dimensions ) { + if (srcBuffer.dim[srcBuffer.dimensions - 1].extent != 1 && dstBuffer.dim[dstBuffer.dimensions - 1].extent != 1) { + MNN_ERROR("srcBuffer dimension not equal to dstBuffer, can't copy buffer\n"); + } + } if (srcTensor->getDimensionType() == dstTensor->getDimensionType()) { for (int i = 0; i < srcBuffer.dimensions; ++i) { MNN_ASSERT(srcBuffer.dim[i].extent <= dstBuffer.dim[i].extent); diff --git a/source/backend/cpu/CPUUnary.cpp b/source/backend/cpu/CPUUnary.cpp index a046b7f4d..b727f1c3e 100644 --- a/source/backend/cpu/CPUUnary.cpp +++ b/source/backend/cpu/CPUUnary.cpp @@ -551,6 +551,7 @@ class CPUUnaryCreator : public CPUBackend::Creator { proc = core->MNNSelectUnaryFunctionForFloat(op->main_as_UnaryOp()->opType(), static_cast(backend)->precisionMode()); } if (nullptr == proc && nullptr == procInt8 && nullptr == op->main_as_UnaryOp()->tableInt8()) { + MNN_ERROR("ERROR: Unary Op can not execute\n"); return nullptr; } return new CPUUnary(backend, proc, procInt8, op); diff --git a/source/backend/metal/AllShader.cpp b/source/backend/metal/AllShader.cpp index 2fb7cacc2..3a695797e 100644 --- a/source/backend/metal/AllShader.cpp +++ b/source/backend/metal/AllShader.cpp @@ -558,235 +558,6 @@ const char* shader_MetalReduction_metal = "define_reduce(max);\n" "define_reduce(prod);\n" ; -const char* shader_MetalBackend_metal = -"struct tensor_shape {\n" -" int size;\n" -" int channel;\n" -" int batch;\n" -" int batch_slices;\n" -"};\n" -"struct Limit {\n" -" uint4 size;\n" -"};\n" -"kernel void upcast_float4(const device M4 *in [[buffer(0)]],\n" -" device float4 *out [[buffer(1)]],\n" -" constant Limit& limit [[buffer(2)]],\n" -" uint gid [[thread_position_in_grid]]) {\n" -" if (gid\n" -"static inline void template_NHWC_to_NC4HW4(const device IType *in,device OType *out,constant tensor_shape &s,uint2 gid) {\n" -" int b=gid.y % s.batch;\n" -" int z=gid.y/s.batch;\n" -" int c=z*4;\n" -" \n" -" auto off_in=in+b*s.size*s.channel+int(gid.x)*s.channel+c;\n" -" auto off_out=out+int(gid.y)*s.size+int(gid.x);\n" -" off_out[0]=OType(c+0(in,out,s,gid);\n" -"}\n" -"kernel void downcast_f_NHWC_to_NC4HW4(const device float *in [[buffer(0)]],\n" -" device M4 *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_u_NHWC_to_NC4HW4(const device uchar *in [[buffer(0)]],\n" -" device uchar4 *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_f_NHWC_to_NC4HW4(const device M *in [[buffer(0)]],\n" -" device M4 *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"template \n" -"static inline void template_NC4HW4_to_NHWC(const device IType *in,device OType *out,constant tensor_shape &s,uint2 gid) {\n" -" int b=gid.y % s.batch;\n" -" int z=gid.y/s.batch;\n" -" int c=z*4;\n" -" auto off_in=in+int(gid.y)*s.size+int(gid.x);\n" -" auto off_out=out+b*s.size*s.channel+int(gid.x)*s.channel+c;\n" -" \n" -" IType v4=off_in[0];\n" -" /* if (1) */ off_out[0]=v4[0];\n" -" if (c+1(in,out,s,gid);\n" -"}\n" -"kernel void downcast_f_NC4HW4_to_NHWC(const device float4 *in [[buffer(0)]],\n" -" device M *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_u_NC4HW4_to_NHWC(const device uchar4 *in [[buffer(0)]],\n" -" device uchar *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_f_NC4HW4_to_NHWC(const device M4 *in [[buffer(0)]],\n" -" device M *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"template \n" -"static inline void template_NCHW_to_NC4HW4(const device IType *in,device OType *out,constant tensor_shape &s,uint2 gid) {\n" -" int b=gid.y % s.batch;\n" -" int z=gid.y/s.batch;\n" -" int c=z*4;\n" -" \n" -" auto off_in=in+(b*s.channel+c)*s.size+int(gid.x);\n" -" auto off_out=out+int(gid.y)*s.size+int(gid.x);\n" -" off_out[0]=OType(c+0(in,out,s,gid);\n" -"}\n" -"kernel void downcast_f_NCHW_to_NC4HW4(const device float *in [[buffer(0)]],\n" -" device M4 *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_u_NCHW_to_NC4HW4(const device uchar *in [[buffer(0)]],\n" -" device uchar4 *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_f_NCHW_to_NC4HW4(const device M *in [[buffer(0)]],\n" -" device M4 *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"template \n" -"static inline void template_NC4HW4_to_NCHW(const device IType *in,device OType *out,constant tensor_shape &s,uint2 gid) {\n" -" int b=gid.y % s.batch;\n" -" int z=gid.y/s.batch;\n" -" int c=z*4;\n" -" \n" -" auto off_in=in+int(gid.y)*s.size+int(gid.x);\n" -" auto off_out=out+(b*s.channel+c)*s.size+int(gid.x);\n" -" IType v4=off_in[0];\n" -" /* if (1) */ off_out[0*s.size]=v4.x;\n" -" if (c+1(in,out,s,gid);\n" -"}\n" -"kernel void downcast_f_NC4HW4_to_NCHW(const device float4 *in [[buffer(0)]],\n" -" device M *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_u_NC4HW4_to_NCHW(const device uchar4 *in [[buffer(0)]],\n" -" device uchar *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"kernel void cvt_f_NC4HW4_to_NCHW(const device M4 *in [[buffer(0)]],\n" -" device M *out [[buffer(1)]],\n" -" constant tensor_shape &s [[buffer(2)]],\n" -" uint2 gid [[thread_position_in_grid]]) {\n" -" if ((int)gid.x(in,out,s,gid);\n" -"}\n" -"template\n" -"static inline void template_NHWC_to_NCHW(const device IType* in,\n" -" device OType* out,constant tensor_shape &s,uint2 gid) {\n" -" int b=gid.y % s.batch;\n" -" int c4=gid.y/s.batch;\n" -" \n" -" auto in_off=(b*s.size+gid.x)*s.channel+c4*4;\n" -" auto out_off=(b*s.channel+c4*4)*s.size+gid.x;\n" -" \n" -" out[out_off]=in[in_off];\n" -" if(c4*4+1(in,out,s,gid);\n" -"}\n" -"template\n" -"static inline void template_NCHW_to_NHWC(const device IType* in,\n" -" device OType* out,constant tensor_shape &s,uint2 gid) {\n" -" int b=gid.y % s.batch;\n" -" int c4=gid.y/s.batch;\n" -" \n" -" auto in_off=(b*s.channel+c4*4)*s.size+gid.x;\n" -" auto out_off=(b*s.size+gid.x)*s.channel+c4*4;\n" -" \n" -" out[out_off]=in[in_off];\n" -" if(c4*4+1(in,out,s,gid);\n" -"}\n" -; const char* shader_MetalSoftmax_metal = "struct softmax_shape {\n" " int inside_size;\n" diff --git a/source/backend/metal/AllShader.hpp b/source/backend/metal/AllShader.hpp index d430897b0..cc9faa50f 100644 --- a/source/backend/metal/AllShader.hpp +++ b/source/backend/metal/AllShader.hpp @@ -5,7 +5,6 @@ extern const char* shader_MetalConvolutionDepthwise_metal; extern const char* shader_MetalConvolutionActivation_metal; extern const char* shader_MetalConvolution_metal; extern const char* shader_MetalReduction_metal; -extern const char* shader_MetalBackend_metal; extern const char* shader_MetalSoftmax_metal; extern const char* shader_MetalLayerNorm_metal; extern const char* shader_MetalConvolutionWinograd_metal; diff --git a/source/backend/metal/MetalBackend.hpp b/source/backend/metal/MetalBackend.hpp index 786a89351..589dd5fff 100644 --- a/source/backend/metal/MetalBackend.hpp +++ b/source/backend/metal/MetalBackend.hpp @@ -235,9 +235,8 @@ class MetalBackend : public Backend { private: mutable id mHostBuffer = nullptr; - void onCopyHostToDevice(const Tensor *src, const Tensor *dst) const; - void onCopyDeviceToHost(const Tensor *src, const Tensor *dst) const; - void onCopyDeviceToDevice(const Tensor *src, const Tensor *dst, id encoder, id shape) const; + // hostmask: 0: no host, 1: src is host, 2: dst is host + void onCopyDeviceToDevice(const Tensor *src, const Tensor *dst, id encoder, id shape, int hostmask = 0) const; bool mUseFloatAsFp16; bool mIsIphone = false; BufferAllocator* mCurrentAllocator = nullptr; diff --git a/source/backend/metal/MetalBackend.mm b/source/backend/metal/MetalBackend.mm index 64187b36c..57d800910 100644 --- a/source/backend/metal/MetalBackend.mm +++ b/source/backend/metal/MetalBackend.mm @@ -342,103 +342,183 @@ MemChunk chunk() override { void MetalBackend::returnConstBuffer(id buffer) const { mHoldBuffers.push(buffer); } - -MTLSize getTensorShape(id shape, const Tensor *tensor) { - int s = 1, c = 1, b = 1; - if (tensor->dimensions() == 4) { - s = tensor->width() * tensor->height(); - c = tensor->channel(); - b = tensor->batch(); - } else if (tensor->dimensions() >= 2){ - for (int i=2; idimensions(); ++i) { +static inline void _getNCPlane(const Tensor* tensor, int& s, int& c, int& b) { + auto format = TensorUtils::getDescribe(tensor)->dimensionFormat; + s = 1, c = 1, b = 1; + b = tensor->length(0); + if (format == MNN_DATA_FORMAT_NHWC) { + c = tensor->length(tensor->dimensions()-1); + for (int i=1; idimensions()-1; ++i) { s *= tensor->length(i); } + } else { c = tensor->length(1); - b = tensor->length(0); + for (int i=2; idimensions(); ++i) { + s *= tensor->length(i); + } } - +} +MTLSize getTensorShape(id shape, const Tensor *tensor) { + auto format = TensorUtils::getDescribe(tensor)->dimensionFormat; + int s, b, c; + _getNCPlane(tensor, s, c, b); int z = UP_DIV(c, 4); // shape - ((int *)shape.contents)[0] = s; + ((int *)shape.contents)[0] = b; ((int *)shape.contents)[1] = c; - ((int *)shape.contents)[2] = b; - ((int *)shape.contents)[3] = b * z; - + ((int *)shape.contents)[2] = s; + ((int *)shape.contents)[3] = 1; + + // stride + if (format == MNN_DATA_FORMAT_NHWC) { + ((int *)shape.contents)[4] = s * c; + ((int *)shape.contents)[5] = 1; + ((int *)shape.contents)[6] = c; + ((int *)shape.contents)[7] = 1; + } else { + ((int *)shape.contents)[4] = s * c; + ((int *)shape.contents)[5] = s; + ((int *)shape.contents)[6] = 1; + ((int *)shape.contents)[7] = 1; + } // threads - MTLSize threads = {(NSUInteger)s, (NSUInteger)b * z, 1}; + MTLSize threads = {(NSUInteger)s * b * z, 1, 1}; return threads; } +static const char* gTranspose = R"metal( +#include +#include +using namespace metal; +struct tensor_shape { + uint4 size; // n, c, plane, 1 + uint4 stride; +}; +kernel void main0(const device IType* in [[buffer(0)]], device OType* out [[buffer(1)]], constant tensor_shape &uConstant [[buffer(2)]], uint gid [[thread_position_in_grid]]) { + int channel = uConstant.size.y; + if (gid < channel * uConstant.size.x * uConstant.size.z) { + int tmp = gid % (channel * uConstant.size.x); + int x = gid / (channel * uConstant.size.x); + int b = tmp / channel; + int c = tmp % channel; + int outPos = b * uConstant.size.y * uConstant.size.z + c * uConstant.size.z + x; + int inPos = b * uConstant.size.y * uConstant.size.z + c + x * uConstant.size.y; + out[outPos] = (OType)(in[inPos]); + } +})metal"; -enum MetalCastType : int { - // no cast - None = 0, - // metal float to float - Up, - // float to metal float - Down +static const char* gNC4HW4Convert = R"metal( +#include +#include +using namespace metal; +struct tensor_shape { + uint4 size; // n, c, plane, 1 + uint4 stride; }; +kernel void main0(const device IType* in [[buffer(0)]], device OType* out [[buffer(1)]], constant tensor_shape &uConstant [[buffer(2)]], uint gid [[thread_position_in_grid]]) { + int channelC4 = (uConstant.size.y + 3) / 4; + if (gid < channelC4 * uConstant.size.x * uConstant.size.z) + { + int3 pos; + pos.z = gid % (channelC4 * uConstant.size.x); + pos.y = gid / (channelC4 * uConstant.size.x); + pos.x = 0; + int batchIndex = pos.z / channelC4; + int zDiv4 = pos.z % channelC4; + + int lastZ = uConstant.size.y / 4; + int cIndex = uConstant.size.y % 4; + + int z = zDiv4*4; + int basicOffset = 0 + + batchIndex*uConstant.stride.x + + z * uConstant.stride.y + + pos.y * uConstant.stride.z + ; +#ifdef MNN_OUTPUT_C4 + OType color = OType(0); + if(zDiv4 == lastZ) + { + if(cIndex == 1) + { + color.r = in[basicOffset+0]; + color.g = 0.0; + color.b = 0.0; + color.a = 0.0; + } + else if(cIndex == 2) + { + color.r = in[basicOffset+0]; + color.g = in[basicOffset+1*uConstant.stride.y]; + color.b = 0.0; + color.a = 0.0; + } + else + { + color.r = in[basicOffset+0]; + color.g = in[basicOffset+1*uConstant.stride.y]; + color.b = in[basicOffset+2*uConstant.stride.y]; + color.a = 0.0; + } + } + else + { + color.r = in[basicOffset+0]; + color.g = in[basicOffset+1*uConstant.stride.y]; + color.b = in[basicOffset+2*uConstant.stride.y]; + color.a = in[basicOffset+3*uConstant.stride.y]; + } -static NSString *kernelForConvert(halide_type_t type, MNN_DATA_FORMAT from, MNN_DATA_FORMAT to, MetalCastType cast) { - if (type.code == halide_type_float) { - NSString *map[3][MNN_DATA_FORMAT_MAX + 1][MNN_DATA_FORMAT_MAX + 1] = { - // none + out[0 + + pos.y + + uConstant.size.x * uConstant.size.z*zDiv4 + + batchIndex*uConstant.size.z + ] = color; +#else + IType color = in[0 + + pos.y + + uConstant.size.x * uConstant.size.z*zDiv4 + + batchIndex*uConstant.size.z + ]; + if(zDiv4 == lastZ) + { + if(cIndex == 1) { - // from MNN_DATA_FORMAT_NCHW - {nil, nil, @"cvt_f_NCHW_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NHWC - {nil, nil, @"cvt_f_NHWC_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NC4HW4 - {@"cvt_f_NC4HW4_to_NCHW", @"cvt_f_NC4HW4_to_NHWC", nil, nil, nil}, - // from MNN_DATA_FORMAT_NHWC4 - {nil, nil, nil, nil, nil}, - // from MNN_DATA_FORMAT_UNKNOWN - {nil, nil, nil, nil, nil}, - }, - // up + out[basicOffset+0*uConstant.stride.y] = color.r; + } + else if(cIndex == 2) { - // from MNN_DATA_FORMAT_NCHW - {nil, nil, @"upcast_f_NCHW_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NHWC - {@"upcast_f_NHWC_to_NCHW", nil, @"upcast_f_NHWC_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NC4HW4 - {@"upcast_f_NC4HW4_to_NCHW", @"upcast_f_NC4HW4_to_NHWC", nil, nil, nil}, - // from MNN_DATA_FORMAT_NHWC4 - {nil, nil, nil, nil, nil}, - // from MNN_DATA_FORMAT_UNKNOWN - {nil, nil, nil, nil, nil}, - }, - // down + out[basicOffset+0*uConstant.stride.y] = color.r; + out[basicOffset+1*uConstant.stride.y] = color.g; + } + else { - // from MNN_DATA_FORMAT_NCHW - {nil, @"downcast_f_NCHW_to_NHWC", @"downcast_f_NCHW_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NHWC - {nil, nil, @"downcast_f_NHWC_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NC4HW4 - {@"downcast_f_NC4HW4_to_NCHW", @"downcast_f_NC4HW4_to_NHWC", nil, nil, nil}, - // from MNN_DATA_FORMAT_NHWC4 - {nil, nil, nil, nil, nil}, - // from MNN_DATA_FORMAT_UNKNOWN - {nil, nil, nil, nil, nil}, - }, - }; - return map[cast][from][to]; - } else { - NSString *map[MNN_DATA_FORMAT_MAX + 1][MNN_DATA_FORMAT_MAX + 1] = { - // from MNN_DATA_FORMAT_NCHW - {nil, nil, @"cvt_u_NCHW_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NHWC - {nil, nil, @"cvt_u_NHWC_to_NC4HW4", nil, nil}, - // from MNN_DATA_FORMAT_NC4HW4 - {@"cvt_u_NC4HW4_to_NCHW", @"cvt_u_NC4HW4_to_NHWC", nil, nil, nil}, - // from MNN_DATA_FORMAT_NHWC4 - {nil, nil, nil, nil, nil}, - // from MNN_DATA_FORMAT_UNKNOWN - {nil, nil, nil, nil, nil}, - }; - return map[from][to]; + out[basicOffset+0*uConstant.stride.y] = color.r; + out[basicOffset+1*uConstant.stride.y] = color.g; + out[basicOffset+2*uConstant.stride.y] = color.b; + } + } + else + { + out[basicOffset+0*uConstant.stride.y] = color.r; + out[basicOffset+1*uConstant.stride.y] = color.g; + out[basicOffset+2*uConstant.stride.y] = color.b; + out[basicOffset+3*uConstant.stride.y] = color.a; + } +#endif } } +)metal"; + +static const char* gCopy = R"metal( +#include +#include +using namespace metal; +kernel void main0(const device IType *in [[buffer(0)]], device OType *out [[buffer(1)]], constant uint4& limit [[buffer(2)]], uint gid [[thread_position_in_grid]]) { + if (gid < limit.x) { + out[int(gid)] = (OType)in[int(gid)]; + } +})metal"; void MetalBackend::onResizeBegin() { mFrameEncodeCache = false; @@ -459,207 +539,146 @@ MTLSize getTensorShape(id shape, const Tensor *tensor) { return mCurrentAllocator->compute(); } -void MetalBackend::onCopyHostToDevice(const Tensor *src, const Tensor *dst) const { - auto ctx = (__bridge MNNMetalContext *)context(); - auto sfmt = TensorUtils::getDescribe(src)->dimensionFormat; - auto dfmt = TensorUtils::getDescribe(dst)->dimensionFormat; - auto device = (id)((MetalRuntimeAllocator::MetalBufferAlloc *) (dst->deviceId()))->getBuffer(); - auto floats = src->getType().code == halide_type_float; - // For command queue from user, need user to make sure last frame's gpu work is ready - bool needWait = !mRuntime->userSync(); - // cast - if (sfmt == dfmt || src->dimensions() <= 1) { - if (floats && mUseFloatAsFp16) { - NSUInteger size = src->elementSize(); - auto sizeC4 = UP_DIV(size, 4); - auto host = this->getHostBuffer(sizeC4 * 4 * sizeof(float)); - if (needWait) { - wait(); - } - memcpy(host.contents, src->host(), src->size()); - unsigned int limits[] = { - (unsigned int)sizeC4, - 1, - 1, - 1 - }; - ::memcpy(mShapeH2D.contents, limits, sizeof(limits)); - auto encoder = [getCommandBufferForBufferCopy() computeCommandEncoder]; - auto pipeline = [ctx pipelineWithName:@"downcast_float4" fp16:mUseFloatAsFp16]; - [encoder setComputePipelineState:pipeline]; - - [encoder setBuffer:host offset:0 atIndex:0]; - [encoder setBuffer:device offset:TensorUtils::getDescribe(dst)->extra.offset atIndex:1]; - [encoder setBuffer:mShapeH2D offset:0 atIndex:2]; - //[ctx dispatchEncoder:encoder threads:{sizeC4, 1, 1} bandwidth:bandwidth]; - std::pair threads; - threads.first = {sizeC4, 1, 1}; - threads.second = {[pipeline maxTotalThreadsPerThreadgroup], 1, 1}; - threads.second.width = threads.second.width <= threads.first.width ? threads.second.width : threads.first.width; - threads.first.width = UP_DIV(threads.first.width, threads.second.width); - [encoder dispatchThreadgroups:threads.first threadsPerThreadgroup:threads.second]; - [encoder endEncoding]; - commit(); - //[ctx wait]; +static std::string _getType(const halide_type_t& type, MNN_DATA_FORMAT format, bool useFp16AsFp32) { + std::string res; + if (type.code == halide_type_float) { + if (useFp16AsFp32) { + res = "half"; } else { - if (needWait) { - wait(); - } - memcpy((uint8_t*)device.contents + TensorUtils::getDescribe(dst)->extra.offset, src->host(), src->size()); + res = "float"; } - } - // convert - else { - - auto buffer = getHostBuffer(src->elementSize() * sizeof(float)); - if (needWait) { - wait(); - } - auto size = getTensorShape(mShapeH2D, src); - memcpy(buffer.contents, src->host(), src->size()); - auto encoder = [getCommandBufferForBufferCopy() computeCommandEncoder]; - auto kernel = kernelForConvert(src->getType(), sfmt, dfmt, Down); - MNN_ASSERT(kernel != nil); // unsupported sfmt to dfmt - auto pipeline = [ctx pipelineWithName:kernel fp16:mUseFloatAsFp16]; - [encoder setComputePipelineState:pipeline]; - - [encoder setBuffer:buffer offset:0 atIndex:0]; - [encoder setBuffer:device offset:TensorUtils::getDescribe(dst)->extra.offset atIndex:1]; - [encoder setBuffer:mShapeH2D offset:0 atIndex:2]; - auto gl = [ctx computeBestGroupAndLocal:pipeline threads:size]; - [encoder dispatchThreadgroups:gl.first threadsPerThreadgroup:gl.second]; - [encoder endEncoding]; - commit(); - //[ctx wait]; - } -} - -void MetalBackend::onCopyDeviceToHost(const Tensor *src, const Tensor *dst) const { - auto ctx = (__bridge MNNMetalContext *)context(); - auto sfmt = TensorUtils::getDescribe(src)->dimensionFormat; - auto dfmt = TensorUtils::getDescribe(dst)->dimensionFormat; - auto device = (id)((MetalRuntimeAllocator::MetalBufferAlloc *)src->deviceId())->getBuffer(); - auto floats = src->getType().code == halide_type_float; - // cast - if (sfmt == dfmt || src->dimensions() <= 1) { - if (floats && mUseFloatAsFp16) { - auto eleSize = dst->elementSize(); - eleSize = UP_DIV(eleSize, 4) * 4; - auto buffer = getHostBuffer(eleSize * dst->getType().bytes()); - - NSUInteger size = src->elementSize(); - auto encoder = [getCommandBufferForBufferCopy() computeCommandEncoder]; - auto pipeline = [ctx pipelineWithName:@"upcast_float4" fp16:mUseFloatAsFp16]; - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:device offset:TensorUtils::getDescribe(src)->extra.offset atIndex:0]; - [encoder setBuffer:buffer offset:0 atIndex:1]; - auto sizeC4 = UP_DIV(size, 4); - unsigned int limits[] = { - (unsigned int)sizeC4, - 1, - 1, - 1 - }; - ::memcpy(mShapeD2H.contents, limits, sizeof(limits)); - [encoder setBuffer:mShapeD2H offset:0 atIndex:2]; - //[ctx dispatchEncoder:encoder threads:{sizeC4, 1, 1} bandwidth:bandwidth]; - std::pair threads; - threads.first = {sizeC4, 1, 1}; - threads.second = {[pipeline maxTotalThreadsPerThreadgroup], 1, 1}; - threads.second.width = threads.second.width <= threads.first.width ? threads.second.width : threads.first.width; - threads.first.width = UP_DIV(threads.first.width, threads.second.width); - [encoder dispatchThreadgroups:threads.first threadsPerThreadgroup:threads.second]; - - [encoder endEncoding]; - commit(); - wait(); - - memcpy(dst->host(), buffer.contents, dst->size()); - } else { - commit(); - wait(); - memcpy(dst->host(), (uint8_t*)device.contents + TensorUtils::getDescribe(src)->extra.offset, dst->size()); + } else { + switch (type.bytes()) { + case 1: + res = "char"; + break; + case 2: + res = "short"; + break; + case 4: + res = "int"; + break; + default: + MNN_ASSERT(false); + break; } } - // convert - else { - auto size = getTensorShape(mShapeD2H, src); - auto buffer = getHostBuffer(dst->size()); - auto encoder = [getCommandBufferForBufferCopy() computeCommandEncoder]; - auto kernel = kernelForConvert(src->getType(), sfmt, dfmt, Up); - MNN_ASSERT(kernel != nil); // unsupported sfmt to dfmt - - auto pipeline = [ctx pipelineWithName:kernel fp16:mUseFloatAsFp16]; - [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:device offset:TensorUtils::getDescribe(src)->extra.offset atIndex:0]; - [encoder setBuffer:buffer offset:0 atIndex:1]; - [encoder setBuffer:mShapeD2H offset:0 atIndex:2]; - auto gl = [ctx computeBestGroupAndLocal:pipeline threads:size]; - [encoder dispatchThreadgroups:gl.first threadsPerThreadgroup:gl.second]; - [encoder endEncoding]; - commit(); - wait(); - memcpy(dst->host(), buffer.contents, dst->size()); + if (format == MNN_DATA_FORMAT_NC4HW4) { + return res + "4"; } + return res; } -static const char* gCopy = R"metal( -#include -#include -using namespace metal; -kernel void main0(const device int4 *in [[buffer(0)]], device int4 *out [[buffer(1)]], constant uint4& limit [[buffer(2)]], uint gid [[thread_position_in_grid]]) { - if (gid < limit.x) { - out[int(gid)] = in[int(gid)]; - } -})metal"; void MetalBackend::onCopyDeviceToDevice(const Tensor *src, const Tensor *dst, - id encoder, id shape) const { + id encoder, id shape, int castType) const { auto ctx = (__bridge MNNMetalContext *)context(); auto standalone = encoder == nil; - encoder = encoder ?: [getCommandBufferForBufferCopy() computeCommandEncoder]; - auto sfmt = TensorUtils::getDescribe(src)->dimensionFormat; - auto dfmt = TensorUtils::getDescribe(dst)->dimensionFormat; - + encoder = encoder ?: [getCommandBufferForBufferCopy() computeCommandEncoder]; + auto sfmt = TensorUtils::getDescribe(src)->dimensionFormat; + auto dfmt = TensorUtils::getDescribe(dst)->dimensionFormat; + if (shape == nil) { + shape = getConstBuffer(8 * sizeof(int)); + } // copy if (sfmt == dfmt || src->dimensions() <= 1) { - auto size = dst->usize(); - if (mUseFloatAsFp16 && dst->getType().code == halide_type_float) { - size = size / 2; - } - size = UP_DIV(size, (4 * sizeof(float))); + auto srcType = _getType(src->getType(), MNN_DATA_FORMAT_NC4HW4, mUseFloatAsFp16 && castType != 1); + auto dstType = _getType(dst->getType(), MNN_DATA_FORMAT_NC4HW4, mUseFloatAsFp16 && castType != 2); + auto size = dst->elementSize(); + size = UP_DIV(size, 4); std::vector keys = { - "copyC4" + "copyC4", + srcType, + dstType }; id pipeline = mRuntime->findPipeline(keys); if (nil == pipeline) { - pipeline = makeComputePipelineWithSourceOption(gCopy, "main0", nil); + MTLCompileOptions *option = [[MTLCompileOptions alloc] init]; + auto dic = [NSMutableDictionary dictionaryWithCapacity:0]; + [dic setValue:@(keys[1].c_str()) forKey:@"IType"]; + [dic setValue:@(keys[2].c_str()) forKey:@"OType"]; + option.preprocessorMacros = dic; + pipeline = makeComputePipelineWithSourceOption(gCopy, "main0", option); mRuntime->insertPipeline(keys, pipeline); } [encoder setComputePipelineState:pipeline]; - if (shape == nil) { - shape = getConstBuffer(4 * sizeof(int)); - } ((uint32_t*)[shape contents])[0] = size; setTensor(src, encoder, 0); setTensor(dst, encoder, 1); [encoder setBuffer:shape offset:0 atIndex:2]; [encoder dispatchThreadgroups:MTLSizeMake(UP_DIV(size, 256), 1, 1) threadsPerThreadgroup:MTLSizeMake(256, 1, 1)]; } - // convert - else { - auto kernel = kernelForConvert(src->getType(), sfmt, dfmt, None); - MNN_ASSERT(kernel != nil); // unsupported sfmt to dfmt - if (shape == nil) { - shape = getConstBuffer(4 * sizeof(int)); + else if (sfmt == MNN_DATA_FORMAT_NC4HW4 || dfmt == MNN_DATA_FORMAT_NC4HW4) { + auto srcType = _getType(src->getType(), sfmt, mUseFloatAsFp16 && castType != 1); + auto dstType = _getType(dst->getType(), dfmt, mUseFloatAsFp16 && castType != 2); + auto normalTensor = dst; + if (dfmt == MNN_DATA_FORMAT_NC4HW4) { + normalTensor = src; + } + // convert C4 / NCHW + std::vector keys = { + "c4convert", + srcType, + dstType + }; + if (dfmt == MNN_DATA_FORMAT_NC4HW4) { + keys.emplace_back("outputc4"); + } + id pipeline = mRuntime->findPipeline(keys); + if (nil == pipeline) { + MTLCompileOptions *option = [[MTLCompileOptions alloc] init]; + auto dic = [NSMutableDictionary dictionaryWithCapacity:0]; + [dic setValue:@(keys[1].c_str()) forKey:@"IType"]; + [dic setValue:@(keys[2].c_str()) forKey:@"OType"]; + if (dfmt == MNN_DATA_FORMAT_NC4HW4) { + [dic setValue:@"1" forKey:@"MNN_OUTPUT_C4"]; + } + option.preprocessorMacros = dic; + pipeline = makeComputePipelineWithSourceOption(gNC4HW4Convert, "main0", option); + mRuntime->insertPipeline(keys, pipeline); } - - auto size = getTensorShape(shape, src); - auto pipeline = [ctx pipelineWithName:kernel fp16:mUseFloatAsFp16]; [encoder setComputePipelineState:pipeline]; - [encoder setBuffer:( id)((MetalRuntimeAllocator::MetalBufferAlloc *)(src->buffer().device))->getBuffer() offset:TensorUtils::getDescribe(src)->extra.offset atIndex:0]; - [encoder setBuffer:( id)((MetalRuntimeAllocator::MetalBufferAlloc *)(dst->buffer().device))->getBuffer() offset:TensorUtils::getDescribe(dst)->extra.offset atIndex:1]; + auto size = getTensorShape(shape, normalTensor); + MetalBackend::setTensor(src, encoder, 0); + MetalBackend::setTensor(dst, encoder, 1); [encoder setBuffer:shape offset:0 atIndex:2]; auto gl = [ctx computeBestGroupAndLocal:pipeline threads:size]; [encoder dispatchThreadgroups:gl.first threadsPerThreadgroup:gl.second]; + } else { + // NCHW <-> NHWC + auto srcType = _getType(src->getType(), sfmt, mUseFloatAsFp16 && castType != 1); + auto dstType = _getType(dst->getType(), dfmt, mUseFloatAsFp16 && castType != 2); + std::vector keys = { + "transpose", + srcType, + dstType + }; + id pipeline = mRuntime->findPipeline(keys); + if (nil == pipeline) { + MTLCompileOptions *option = [[MTLCompileOptions alloc] init]; + auto dic = [NSMutableDictionary dictionaryWithCapacity:0]; + [dic setValue:@(keys[1].c_str()) forKey:@"IType"]; + [dic setValue:@(keys[2].c_str()) forKey:@"OType"]; + option.preprocessorMacros = dic; + pipeline = makeComputePipelineWithSourceOption(gTranspose, "main0", option); + mRuntime->insertPipeline(keys, pipeline); + } + [encoder setComputePipelineState:pipeline]; + int n, c, plane; + _getNCPlane(dst, plane, c, n); + auto shapePtr = (uint32_t*)shape.contents; + shapePtr[0] = n; + shapePtr[3] = 1; + if (MNN_DATA_FORMAT_NHWC == dfmt) { + shapePtr[1] = plane; + shapePtr[2] = c; + } else { + shapePtr[1] = c; + shapePtr[2] = plane; + } + auto size = plane * n * c; + setTensor(src, encoder, 0); + setTensor(dst, encoder, 1); + [encoder setBuffer:shape offset:0 atIndex:2]; + [encoder dispatchThreadgroups:MTLSizeMake(UP_DIV(size, 256), 1, 1) threadsPerThreadgroup:MTLSizeMake(256, 1, 1)]; } if (standalone) { @@ -690,15 +709,58 @@ kernel void main0(const device int4 *in [[buffer(0)]], device int4 *out [[buffer if (!src->buffer().host && !dst->buffer().host) { onCopyDeviceToDevice(src, dst, encoder, shape); - } else if (!src->buffer().host && dst->buffer().host) { - onCopyDeviceToHost(src, dst); + return; + } + auto sfmt = TensorUtils::getDescribe(src)->dimensionFormat; + auto dfmt = TensorUtils::getDescribe(dst)->dimensionFormat; + bool formatDiff = sfmt != dfmt && src->dimensions() > 1; + auto floats = src->getType().code == halide_type_float; + bool dataTypeDiff = floats && mUseFloatAsFp16; + bool needConvert = formatDiff || dataTypeDiff; + + if (!src->buffer().host && dst->buffer().host) { + auto device = (id)((MetalRuntimeAllocator::MetalBufferAlloc *)src->deviceId())->getBuffer(); + auto devicePtr = (uint8_t*)device.contents + TensorUtils::getDescribe(src)->extra.offset; + if (needConvert) { + auto tDst = const_cast(dst); + auto tmpBuffer = getHostBuffer(dst->usize()); + MetalRuntimeAllocator::MetalBufferAlloc tmp(tmpBuffer); + TensorUtils::getDescribe(tDst)->extra.offset = 0; + tDst->buffer().device = (uint64_t)(&tmp); + onCopyDeviceToDevice(src, dst, nullptr, nullptr, 2); + tDst->buffer().device = 0; + devicePtr = (uint8_t*)tmpBuffer.contents; + commit(); + } + wait(); + ::memcpy(dst->host(), devicePtr, dst->usize()); + return; + } + if (src->buffer().host && !dst->buffer().host) { + auto device = (id)((MetalRuntimeAllocator::MetalBufferAlloc *)dst->deviceId())->getBuffer(); + auto devicePtr = (uint8_t*)device.contents + TensorUtils::getDescribe(dst)->extra.offset; - } else if (src->buffer().host && !dst->buffer().host) { - onCopyHostToDevice(src, dst); - - } else { - MNN_ASSERT(false); // should not be handled here + // For command queue from user, need user to make sure last frame's gpu work is ready + bool needWait = !mRuntime->userSync(); + if (needWait) { + wait(); + } + auto srcSize = src->usize(); + if (needConvert) { + auto tmpBuffer = getHostBuffer(srcSize); + ::memcpy(tmpBuffer.contents, src->host(), srcSize); + MetalRuntimeAllocator::MetalBufferAlloc tmp(tmpBuffer); + auto tSrc = const_cast(src); + TensorUtils::getDescribe(tSrc)->extra.offset = 0; + tSrc->buffer().device = (uint64_t)(&tmp); + onCopyDeviceToDevice(tSrc, dst, nullptr, nullptr, 1); + tSrc->buffer().device = 0; + } else { + ::memcpy(devicePtr, src->host(), srcSize); + } + return; } + MNN_ASSERT(false); // should not be handled here } int MetalBackend::onSync(Tensor::MapType mtype, bool toCpu, const Tensor* dstTensor) { flushEncoder(); diff --git a/source/backend/metal/ShaderMap.cpp b/source/backend/metal/ShaderMap.cpp index 0b6b74780..bcdbe5e88 100644 --- a/source/backend/metal/ShaderMap.cpp +++ b/source/backend/metal/ShaderMap.cpp @@ -7,7 +7,6 @@ mMaps.insert(std::make_pair("shader_MetalConvolutionDepthwise_metal", shader_Met mMaps.insert(std::make_pair("shader_MetalConvolutionActivation_metal", shader_MetalConvolutionActivation_metal)); mMaps.insert(std::make_pair("shader_MetalConvolution_metal", shader_MetalConvolution_metal)); mMaps.insert(std::make_pair("shader_MetalReduction_metal", shader_MetalReduction_metal)); -mMaps.insert(std::make_pair("shader_MetalBackend_metal", shader_MetalBackend_metal)); mMaps.insert(std::make_pair("shader_MetalSoftmax_metal", shader_MetalSoftmax_metal)); mMaps.insert(std::make_pair("shader_MetalLayerNorm_metal", shader_MetalLayerNorm_metal)); mMaps.insert(std::make_pair("shader_MetalConvolutionWinograd_metal", shader_MetalConvolutionWinograd_metal)); diff --git a/source/backend/metal/shader/MetalBackend.metal b/source/backend/metal/shader/MetalBackend.metal deleted file mode 100644 index 973f50fc4..000000000 --- a/source/backend/metal/shader/MetalBackend.metal +++ /dev/null @@ -1,235 +0,0 @@ -struct tensor_shape { - int size; - int channel; - int batch; - int batch_slices; -}; - -struct Limit { - uint4 size; -}; -kernel void upcast_float4(const device ftype4 *in [[buffer(0)]], - device float4 *out [[buffer(1)]], - constant Limit& limit [[buffer(2)]], - uint gid [[thread_position_in_grid]]) { - if (gid < limit.size.x) { - out[int(gid)] = float4(in[int(gid)]); - } -} -kernel void downcast_float4(const device float4 *in [[buffer(0)]], - device ftype4 *out [[buffer(1)]], - constant Limit& limit [[buffer(2)]], - uint gid [[thread_position_in_grid]]) { - if (gid < limit.size.x) { - out[int(gid)] = ftype4(in[int(gid)]); - } -} - -template -static inline void template_NHWC_to_NC4HW4(const device IType *in, device OType *out, constant tensor_shape &s, uint2 gid) { - int b = gid.y % s.batch; - int z = gid.y / s.batch; - int c = z * 4; - - auto off_in = in + b * s.size * s.channel + int(gid.x) * s.channel + c; - auto off_out = out + int(gid.y) * s.size + int(gid.x); - off_out[0] = OType(c + 0 < s.channel ? off_in[0] : 0, - c + 1 < s.channel ? off_in[1] : 0, - c + 2 < s.channel ? off_in[2] : 0, - c + 3 < s.channel ? off_in[3] : 0); -} -kernel void upcast_f_NHWC_to_NC4HW4(const device ftype *in [[buffer(0)]], - device float4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NHWC_to_NC4HW4(in, out, s, gid); -} -kernel void downcast_f_NHWC_to_NC4HW4(const device float *in [[buffer(0)]], - device ftype4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NHWC_to_NC4HW4(in, out, s, gid); -} -kernel void cvt_u_NHWC_to_NC4HW4(const device uchar *in [[buffer(0)]], - device uchar4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NHWC_to_NC4HW4(in, out, s, gid); -} -kernel void cvt_f_NHWC_to_NC4HW4(const device ftype *in [[buffer(0)]], - device ftype4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NHWC_to_NC4HW4(in, out, s, gid); -} - -template -static inline void template_NC4HW4_to_NHWC(const device IType *in, device OType *out, constant tensor_shape &s, uint2 gid) { - int b = gid.y % s.batch; - int z = gid.y / s.batch; - int c = z * 4; - auto off_in = in + int(gid.y) * s.size + int(gid.x); - auto off_out = out + b * s.size * s.channel + int(gid.x) * s.channel + c; - - IType v4 = off_in[0]; - /* if (1) */ off_out[0] = v4[0]; - if (c + 1 < s.channel) off_out[1] = v4[1]; - if (c + 2 < s.channel) off_out[2] = v4[2]; - if (c + 3 < s.channel) off_out[3] = v4[3]; -} -kernel void upcast_f_NC4HW4_to_NHWC(const device ftype4 *in [[buffer(0)]], - device float *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NHWC(in, out, s, gid); -} -kernel void downcast_f_NC4HW4_to_NHWC(const device float4 *in [[buffer(0)]], - device ftype *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NHWC(in, out, s, gid); -} -kernel void cvt_u_NC4HW4_to_NHWC(const device uchar4 *in [[buffer(0)]], - device uchar *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NHWC(in, out, s, gid); -} -kernel void cvt_f_NC4HW4_to_NHWC(const device ftype4 *in [[buffer(0)]], - device ftype *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NHWC(in, out, s, gid); -} - -template -static inline void template_NCHW_to_NC4HW4(const device IType *in, device OType *out, constant tensor_shape &s, uint2 gid) { - int b = gid.y % s.batch; - int z = gid.y / s.batch; - int c = z * 4; - - auto off_in = in + (b * s.channel + c) * s.size + int(gid.x); - auto off_out = out + int(gid.y) * s.size + int(gid.x); - off_out[0] = OType(c + 0 < s.channel ? off_in[0 * s.size] : 0.0h, - c + 1 < s.channel ? off_in[1 * s.size] : 0.0h, - c + 2 < s.channel ? off_in[2 * s.size] : 0.0h, - c + 3 < s.channel ? off_in[3 * s.size] : 0.0h); -} -kernel void upcast_f_NCHW_to_NC4HW4(const device ftype *in [[buffer(0)]], - device float4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NCHW_to_NC4HW4(in, out, s, gid); -} -kernel void downcast_f_NCHW_to_NC4HW4(const device float *in [[buffer(0)]], - device ftype4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NCHW_to_NC4HW4(in, out, s, gid); -} -kernel void cvt_u_NCHW_to_NC4HW4(const device uchar *in [[buffer(0)]], - device uchar4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NCHW_to_NC4HW4(in, out, s, gid); -} -kernel void cvt_f_NCHW_to_NC4HW4(const device ftype *in [[buffer(0)]], - device ftype4 *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NCHW_to_NC4HW4(in, out, s, gid); -} - -template -static inline void template_NC4HW4_to_NCHW(const device IType *in, device OType *out, constant tensor_shape &s, uint2 gid) { - int b = gid.y % s.batch; - int z = gid.y / s.batch; - int c = z * 4; - - auto off_in = in + int(gid.y) * s.size + int(gid.x); - auto off_out = out + (b * s.channel + c) * s.size + int(gid.x); - IType v4 = off_in[0]; - /* if (1) */ off_out[0 * s.size] = v4.x; - if (c + 1 < s.channel) off_out[1 * s.size] = v4.y; - if (c + 2 < s.channel) off_out[2 * s.size] = v4.z; - if (c + 3 < s.channel) off_out[3 * s.size] = v4.w; -} -kernel void upcast_f_NC4HW4_to_NCHW(const device ftype4 *in [[buffer(0)]], - device float *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NCHW(in, out, s, gid); -} -kernel void downcast_f_NC4HW4_to_NCHW(const device float4 *in [[buffer(0)]], - device ftype *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NCHW(in, out, s, gid); -} -kernel void cvt_u_NC4HW4_to_NCHW(const device uchar4 *in [[buffer(0)]], - device uchar *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NCHW(in, out, s, gid); -} -kernel void cvt_f_NC4HW4_to_NCHW(const device ftype4 *in [[buffer(0)]], - device ftype *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NC4HW4_to_NCHW(in, out, s, gid); -} - -template -static inline void template_NHWC_to_NCHW(const device IType* in, - device OType* out, constant tensor_shape &s, uint2 gid) { - int b = gid.y % s.batch; - int c4 = gid.y / s.batch; - - auto in_off = (b * s.size + gid.x) * s.channel + c4 * 4; - auto out_off = (b * s.channel + c4 * 4) * s.size + gid.x; - - out[out_off] = in[in_off]; - if(c4 * 4 + 1 < s.channel) { - out[out_off + s.size] = in[in_off + 1]; - } - if(c4 * 4 + 2 < s.channel) { - out[out_off + s.size * 2] = in[in_off + 2]; - } - if(c4 * 4 + 3 < s.channel) { - out[out_off + s.size * 3] = in[in_off + 3]; - } -} - -kernel void upcast_f_NHWC_to_NCHW(const device ftype *in [[buffer(0)]], - device float *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NHWC_to_NCHW(in, out, s, gid); -} - -template -static inline void template_NCHW_to_NHWC(const device IType* in, - device OType* out, constant tensor_shape &s, uint2 gid) { - int b = gid.y % s.batch; - int c4 = gid.y / s.batch; - - auto in_off = (b * s.channel + c4 * 4) * s.size + gid.x; - auto out_off = (b * s.size + gid.x) * s.channel + c4 * 4; - - out[out_off] = in[in_off]; - if(c4 * 4 + 1 < s.channel) { - out[out_off + 1] = in[in_off + s.size]; - } - if(c4 * 4 + 2 < s.channel) { - out[out_off + 2] = in[in_off + s.size * 2]; - } - if(c4 * 4 + 3 < s.channel) { - out[out_off + 3] = in[in_off + s.size * 3]; - } -} -kernel void downcast_f_NCHW_to_NHWC(const device float *in [[buffer(0)]], - device ftype *out [[buffer(1)]], - constant tensor_shape &s [[buffer(2)]], - uint2 gid [[thread_position_in_grid]]) { - if ((int)gid.x < s.size && (int)gid.y < s.batch_slices) template_NCHW_to_NHWC(in, out, s, gid); -} diff --git a/source/backend/opencl/core/BufferConvertor.cpp b/source/backend/opencl/core/BufferConvertor.cpp index ab51ef7db..1d649a0b8 100644 --- a/source/backend/opencl/core/BufferConvertor.cpp +++ b/source/backend/opencl/core/BufferConvertor.cpp @@ -405,6 +405,7 @@ bool BufferConvertor::convertToNC4HW4Buffer(const Tensor *buffer, const OpenCLBu auto runtime = mOpenCLRuntime; std::string kernelName; + std::string kernelFile = "buffer_convert_buf"; switch (type) { case CONV2D_FILTER: #ifdef MNN_LOW_MEMORY @@ -413,6 +414,7 @@ bool BufferConvertor::convertToNC4HW4Buffer(const Tensor *buffer, const OpenCLBu MNN_ERROR("For Opencl Backend, only support low memory mode of int8 or int4 dequantization currently.\n"); MNN_ASSERT(false); } + kernelFile = "buffer_convert_quant"; // shared part for all cases if (quantBit == 8) { kernelName = "conv2d_filter_buffer_to_nc4hw4_buffer_int8"; //NC4HW4 (1, 4*ic/4, kw*kh*oc/4, 1)*4 @@ -452,7 +454,7 @@ bool BufferConvertor::convertToNC4HW4Buffer(const Tensor *buffer, const OpenCLBu } else {/* More types to be supported. */} } #endif - mBufferToImageKernel = runtime->buildKernelWithCache("buffer_convert_buf", kernelName, buildOptions, buffer, image); + mBufferToImageKernel = runtime->buildKernelWithCache(kernelFile, kernelName, buildOptions, buffer, image); } auto kernel = mBufferToImageKernel->get(); diff --git a/source/backend/opencl/core/OpenCLGemmTune.cpp b/source/backend/opencl/core/OpenCLGemmTune.cpp new file mode 100644 index 000000000..870bf7530 --- /dev/null +++ b/source/backend/opencl/core/OpenCLGemmTune.cpp @@ -0,0 +1,417 @@ +// +// OpenCLGemmTune.cpp +// MNN +// +// Created by MNN on 2024/05/30. +// Copyright © 2018, Alibaba Group Holding Limited +// + +#include "backend/opencl/core/OpenCLRunningUtils.hpp" +#include +#include +#include +#include +#include "core/Macro.h" + +namespace MNN { +namespace OpenCL { + + +static void generateCombinations(const std::vector> &candidates, std::vector ¤tCombination, std::vector> &totalCombinations, int depth) { + if (depth == candidates.size()) { + totalCombinations.emplace_back(currentCombination); + return; + } + + // Loop all candidates + for (int i = 0; i < candidates[depth].size(); i++) { + currentCombination[depth] = candidates[depth][i]; + // Recurrence + generateCombinations(candidates, currentCombination, totalCombinations, depth + 1); + } +} + + +static bool isCandidateValid(uint32_t kwg, uint32_t kwi, uint32_t mwg, uint32_t mdimc, uint32_t vwm, uint32_t nwg, uint32_t ndimc, uint32_t vwn, uint32_t mdima, uint32_t ndimb, uint32_t sa, uint32_t sb, OpenCLRuntime *runtime, const std::vector& gemmSize) { + // problem size align + if(gemmSize[0] % mwg != 0 || gemmSize[1] % nwg != 0 || gemmSize[2] % kwg != 0) { + return false; + } + // mwg nwg only for M N equal to 16 + if((gemmSize[0] > 16 && mwg == 16) || (gemmSize[1] > 16 && nwg == 16)) { + return false; + } + // params align + if(kwg % kwi != 0) { + return false; + } + if(mwg % (mdimc * vwm) != 0 || mwg % (mdima * vwm) != 0) { + return false; + } + if(nwg % (ndimc * vwn) != 0 || nwg % (ndimb * vwn) != 0) { + return false; + } + uint32_t kdima = (mdimc * ndimc) / mdima; + uint32_t kdimb = (mdimc * ndimc) / ndimb; + if(kwg % kdima != 0 || kwg % kdimb != 0) { + return false; + } + if(mdimc != mdima || ndimc != ndimb) { + return false; + } + if(sa != sb) { + return false; + } + + // local memory limit + uint32_t local_mem_size = 0; + if(sa) { + local_mem_size += kwg * mwg; + } + if(sb) { + local_mem_size += kwg * nwg; + } + if(runtime->isSupportedFP16()) { + local_mem_size *= 2; + } else { + local_mem_size *= 4; + } + if(local_mem_size > runtime->getMaxLocalMem()) { + return false; + } + + // local size limit + if(mdimc * ndimc > runtime->MaxWorkGroupSize()) { + return false; + } + + // reduce total candidate number + if(mdimc != mdima || ndimc != ndimb) { + return false; + } + bool totalLarge = 1.0 * gemmSize[0] / 1024 * gemmSize[1] / 1024 * gemmSize[2] / 1024 >= 0.5; + bool dimLarge = gemmSize[0] > 128 && gemmSize[1] > 128 && gemmSize[2] > 128; + if(totalLarge && dimLarge) { + if(mwg * nwg < 128 * 64) { + return false; + } + if(mdimc * ndimc < 16 * 8) { + return false; + } + if(vwm * vwn < 4 * 4) { + return false; + } + } else { + if(mwg * nwg > 128 * 64) { + return false; + } + if(mdimc * ndimc > 16 * 8) { + return false; + } + if(vwm * vwn > 4 * 4) { + return false; + } + } + + return true; +} + +std::vector getGemmParams(const std::vector &gemmSize, const std::vector tensorMemory, + OpenCLRuntime *runtime) { + MNN_ASSERT(gemmSize.size() == 5); // M, N, K, Layout, B + MNN_ASSERT(gemmSize[0] % 16 == 0); + MNN_ASSERT(gemmSize[1] % 16 == 0); + MNN_ASSERT(gemmSize[2] % 16 == 0); + + MNN_ASSERT(tensorMemory.size() == 3); + auto& tunedGemmParams = runtime->tunedGemmParamsMap(); + + + std::vector info(gemmSize); + uint32_t isFp16 = runtime->isSupportedFP16(); + info.emplace_back(isFp16); + + if (tunedGemmParams.find(info) != tunedGemmParams.end()) { + return tunedGemmParams[info]; + } + + if(runtime->getCLTuneLevel() == None) { + auto getMaxDivisor = [](uint32_t num) -> uint32_t { + std::vector divisors = {128, 64, 32}; + for (const auto& divisor : divisors) { + if (num % divisor == 0) { + return divisor; + } + } + return 16; + }; + float multiNum = 1.0 * gemmSize[0] / 512.0 * gemmSize[1] / 512.0 * gemmSize[2] / 512.0; + int maxDivsorM = getMaxDivisor(gemmSize[0]); + int maxDivsorN = getMaxDivisor(gemmSize[1]); + + if(gemmSize[4] == 1) {// Gemm + if(gemmSize[0] >= 256 && gemmSize[1] >= 256 && gemmSize[2] >= 256) { + if(multiNum > 8.0) { + if(maxDivsorM >= 128 && maxDivsorN >= 64) { + return {0, 1, 16, 2, 16, 16, 128, 8, 8, 64, 0, 0, 0, 1, 8, 8}; + } + } + if(maxDivsorM >= 64 && maxDivsorN >= 64) { + return {0, 1, 16, 2, 8, 8, 64, 8, 8, 64, 0, 0, 0, 1, 8, 8}; + } + } + } else {// BatchGemm + if(maxDivsorM >= 64 && maxDivsorN >= 128) { + return {0, 1, 16, 2, 16, 16, 64, 8, 8, 128, 0, 0, 1, 0, 2, 8}; + } else if(maxDivsorM >= 64 && maxDivsorN >= 64) { + return {0, 1, 16, 2, 8, 8, 64, 8, 8, 64, 0, 0, 1, 0, 4, 4}; + } + } + return {0, 1, 16, 2, 4, 4, 16, 4, 4, 16, 0, 0, 1, 0, 2, 2}; + } + + std::vector> totalCombinations; // save total candidate combinations + std::vector params_prefer = {0, 1, 16, 2, 4, 4, 16, 4, 4, 16, 0, 0, 1, 0, 2, 2}; + totalCombinations.emplace_back(params_prefer); + uint32_t min_cost = UINT_MAX; + + if(runtime->getCLTuneLevel() >= Normal) { + // set candidates + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 64 , 8 , 8 , 128, 0, 0, 1, 1, 2, 8});//12 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 0, 0, 8, 8});//11 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 0, 8, 8});//4 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 1, 2, 8});//2 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 128, 0, 0, 0, 1, 8, 8}); + totalCombinations.push_back({0, 1, 16, 2, 8 , 8 , 16 , 8 , 8 , 128, 0, 0, 0, 0, 2, 8}); + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 64 , 8 , 8 , 32 , 0, 0, 0, 0, 4, 4}); + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 32 , 0, 0, 1, 0, 4, 4});//1 + totalCombinations.push_back({0, 1, 16, 2, 8, 8 , 32 , 8 , 8 , 128, 0, 0, 1, 0, 2, 8});//2 + + if(runtime->getCLTuneLevel() == Normal) { + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 64 , 8 , 8 , 128, 0, 0, 1, 1, 2, 8});//10 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 0, 0, 8, 8});//6 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 0, 1, 8, 8});//6 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 0, 2, 8});//4 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 1, 8, 8});//4 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 0, 1, 8, 8});//4 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 0, 2, 8});//3 + totalCombinations.push_back({0, 1, 16, 2, 8, 8 , 64 , 8 , 8 , 64 , 0, 0, 1, 0, 2, 8});//1 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 1, 4, 4});//1 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 0, 8, 8});//2 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 64 , 8 , 8 , 128, 0, 0, 1, 0, 2, 8});//3 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 32 , 0, 0, 1, 1, 4, 4});//1 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 32 , 0, 0, 1, 1, 4, 4});//1 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 16, 16, 128, 0, 0, 0, 0, 8, 8});//1 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 16, 16, 128, 0, 0, 0, 0, 8, 8});//2 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 16, 16, 128, 0, 0, 0, 1, 8, 8});//2 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 1, 8, 8});//2 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 16, 16, 128, 0, 0, 1, 0, 8, 8});//1 + totalCombinations.push_back({0, 1, 32, 2, 8 , 8 , 16 , 8 , 8 , 128, 0, 0, 1, 0, 2, 8});//1 + totalCombinations.push_back({0, 1, 32, 2, 8 , 8 , 16 , 8 , 8 , 128, 0, 0, 1, 1, 2, 8});//1 + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 64 , 8 , 8 , 32 , 0, 0, 0, 1, 4, 4});//1 + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 64 , 8 , 8 , 32 , 0, 0, 0, 1, 4, 4}); + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 64 , 8 , 8 , 32 , 0, 0, 1, 0, 4, 4}); + totalCombinations.push_back({0, 1, 16, 2, 8 , 8 , 16 , 8 , 8 , 128, 0, 0, 1, 0, 2, 8}); + totalCombinations.push_back({0, 1, 32, 2, 8 , 8 , 16 , 8 , 8 , 128, 0, 0, 0, 0, 2, 8}); + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 1, 2, 8}); + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 64 , 0, 0, 1, 0, 4, 8}); + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 8 , 8 , 128, 0, 0, 0, 0, 8, 8}); + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 128, 0, 0, 0, 1, 8, 8}); + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 128, 0, 0, 0, 0, 8, 8}); + totalCombinations.push_back({0, 1, 32, 2, 16, 16, 128, 8 , 8 , 128, 0, 0, 1, 1, 8, 8}); + totalCombinations.push_back({0, 1, 16, 2, 16, 16, 128, 16, 16, 128, 0, 0, 1, 0, 8, 8}); + } + } else { + // get all combinations + std::vector> candidates = { + {0}, // GEMMK + {16, 32, 64, 128}, // MWG + {16, 32, 64, 128}, // NWG + {16, 32}, // KWG + {8, 16}, // MDIMC + {8, 16}, // NDIMC + {8, 16}, // MDIMA + {8, 16}, // NDIMB + {2}, // KWI + {2, 4, 8}, // VWM + {2, 4, 8}, // VWN + {0, 1}, // STRM + {0, 1}, // STRN + {0}, // SA + {0}, // SB + {1} // KREG + }; + + std::vector currentCombination(candidates.size()); + generateCombinations(candidates, currentCombination, totalCombinations, 0); + } + + for(int i = 0; i < totalCombinations.size(); i++) { + uint32_t gemmk = totalCombinations[i][0]; + uint32_t kreg = totalCombinations[i][1]; + uint32_t kwg = totalCombinations[i][2]; + uint32_t kwi = totalCombinations[i][3]; + uint32_t mdima = totalCombinations[i][4]; + uint32_t mdimc = totalCombinations[i][5]; + uint32_t mwg = totalCombinations[i][6]; + uint32_t ndimb = totalCombinations[i][7]; + uint32_t ndimc = totalCombinations[i][8]; + uint32_t nwg = totalCombinations[i][9]; + uint32_t sa = totalCombinations[i][10]; + uint32_t sb = totalCombinations[i][11]; + uint32_t strm = totalCombinations[i][12]; + uint32_t strn = totalCombinations[i][13]; + uint32_t vwm = totalCombinations[i][14]; + uint32_t vwn = totalCombinations[i][15]; + + if(isCandidateValid(kwg, kwi, mwg, mdimc, vwm, nwg, ndimc, vwn, mdima, ndimb, sa, sb, runtime, gemmSize)) { + + std::set buildOptions; + buildOptions.clear(); + buildOptions.emplace("-DGEMMK=" + std::to_string(gemmk)); + buildOptions.emplace("-DKREG=" + std::to_string(kreg)); + buildOptions.emplace("-DKWG=" + std::to_string(kwg)); + buildOptions.emplace("-DKWI=" + std::to_string(kwi)); + buildOptions.emplace("-DMDIMA=" + std::to_string(mdima)); + buildOptions.emplace("-DMDIMC=" + std::to_string(mdimc)); + buildOptions.emplace("-DMWG=" + std::to_string(mwg)); + buildOptions.emplace("-DNDIMB=" + std::to_string(ndimb)); + buildOptions.emplace("-DNDIMC=" + std::to_string(ndimc)); + buildOptions.emplace("-DNWG=" + std::to_string(nwg)); + buildOptions.emplace("-DSA=" + std::to_string(sa)); + buildOptions.emplace("-DSB=" + std::to_string(sb)); + buildOptions.emplace("-DSTRM=" + std::to_string(strm)); + buildOptions.emplace("-DSTRN=" + std::to_string(strn)); + buildOptions.emplace("-DVWM=" + std::to_string(vwm)); + buildOptions.emplace("-DVWN=" + std::to_string(vwn)); + + if(gemmSize[3] >= 4) { + buildOptions.emplace(" -DOUTPUTMN"); + } + if(runtime->getGpuType() == GpuType::ADRENO) { + buildOptions.emplace(" -DUSE_CL_MAD=1"); + buildOptions.emplace(" -DRELAX_WORKGROUP_SIZE=1"); + } + + if(runtime->isSupportedFP16()){ + buildOptions.emplace(" -DPRECISION=16"); + } else { + buildOptions.emplace(" -DPRECISION=32"); + } + + int localM = mdimc; + int localN = ndimc; + + std::shared_ptr kernel = runtime->buildKernel("matmul_params_buf", "Xgemm", buildOptions); + if(kernel == nullptr) { + continue; + } + if(gemmSize[4] > 1) { + kernel = runtime->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); + if(kernel == nullptr) { + continue; + } + } + + if(localM * localN > runtime->getMaxWorkGroupSize(kernel)) { + continue; + } + int tileM = mwg; + int tileN = nwg; + int out_per_thread_m = tileM / localM; + int out_per_thread_n = tileN / localN; + + std::vector globalWorkSize = {static_cast(gemmSize[0]/out_per_thread_m), static_cast(gemmSize[1]/out_per_thread_n), gemmSize[4]}; + std::vector localWorkSize = {static_cast(localM), static_cast(localN), 1}; + + float alpha = 1.0; + float beta = 0.0f; + // A: [n, l, e] + // B: [n, l, h] + int offset_a = 0; + int offset_b = 0; + int offset_c = 0; + + cl::Event event; + int idx = 0; + cl_int ret = CL_SUCCESS; + ret |= kernel->get().setArg(idx++, static_cast(gemmSize[0])); + ret |= kernel->get().setArg(idx++, static_cast(gemmSize[1])); + ret |= kernel->get().setArg(idx++, static_cast(gemmSize[2])); + ret |= kernel->get().setArg(idx++, alpha); + ret |= kernel->get().setArg(idx++, beta); + if(gemmSize[4] > 1) { + ret |= kernel->get().setArg(idx++, tensorMemory[0]); + ret |= kernel->get().setArg(idx++, gemmSize[0]); + ret |= kernel->get().setArg(idx++, gemmSize[2]); + ret |= kernel->get().setArg(idx++, tensorMemory[1]); + ret |= kernel->get().setArg(idx++, gemmSize[1]); + ret |= kernel->get().setArg(idx++, gemmSize[2]); + ret |= kernel->get().setArg(idx++, tensorMemory[2]); + ret |= kernel->get().setArg(idx++, gemmSize[0]); + ret |= kernel->get().setArg(idx++, gemmSize[1]); + + MNN_CHECK_CL_SUCCESS(ret, "setArg getGemmParams XgemmBatchhed Kernel"); + + auto res = CL_SUCCESS; + res = runtime->commandQueue().enqueueNDRangeKernel(kernel->get(), cl::NullRange, {globalWorkSize[0], globalWorkSize[1], globalWorkSize[2]}, {localWorkSize[0], localWorkSize[1], localWorkSize[2]}, nullptr, &event); + if (res != CL_SUCCESS) { + MNN_PRINT("XgemmBatched params tune error: %d\n", res); + continue; + } + } else { + ret |= kernel->get().setArg(idx++, tensorMemory[0]); + ret |= kernel->get().setArg(idx++, tensorMemory[1]); + ret |= kernel->get().setArg(idx++, tensorMemory[2]); + ret |= kernel->get().setArg(idx++, offset_a); + ret |= kernel->get().setArg(idx++, offset_b); + ret |= kernel->get().setArg(idx++, offset_c); + + MNN_CHECK_CL_SUCCESS(ret, "setArg getGemmParams Xgemm Kernel"); + + auto res = CL_SUCCESS; + res = runtime->commandQueue().enqueueNDRangeKernel(kernel->get(), cl::NullRange, {globalWorkSize[0], globalWorkSize[1]}, {localWorkSize[0], localWorkSize[1]}, nullptr, &event); + if (res != CL_SUCCESS) { + MNN_PRINT("Xgemm params tune error: %d\n", res); + continue; + } + } + + + int cost_time = (int)runtime->getCostTime(&event); + if(cost_time < min_cost) { + min_cost = cost_time; + params_prefer[0] = gemmk; + params_prefer[1] = kreg; + params_prefer[2] = kwg; + params_prefer[3] = kwi; + params_prefer[4] = mdima; + params_prefer[5] = mdimc; + params_prefer[6] = mwg; + params_prefer[7] = ndimb; + params_prefer[8] = ndimc; + params_prefer[9] = nwg; + params_prefer[10] = sa; + params_prefer[11] = sb; + params_prefer[12] = strm; + params_prefer[13] = strn; + params_prefer[14] = vwm; + params_prefer[15] = vwn; + +// for(auto &iter : params_prefer) { +// MNN_PRINT("%d ", iter); +// } +// MNN_PRINT(": %d us, shape:%d %d %d batch:%d, flops:%f GFLOPS\n", min_cost, gemmSize[0], gemmSize[1], gemmSize[2], gemmSize[4], 2.0 / 1000.0 * gemmSize[0] * gemmSize[1] * gemmSize[2] * gemmSize[4] / min_cost); + } + } + } + + if (tunedGemmParams.find(info) == tunedGemmParams.end()) { + tunedGemmParams.insert(std::make_pair(info, params_prefer)); + } + + return params_prefer; +} + +} // namespace OpenCL +} // namespace MNN diff --git a/source/backend/opencl/core/OpenCLOPRegister.cpp b/source/backend/opencl/core/OpenCLOPRegister.cpp index 538a6963d..9f244d651 100644 --- a/source/backend/opencl/core/OpenCLOPRegister.cpp +++ b/source/backend/opencl/core/OpenCLOPRegister.cpp @@ -61,6 +61,9 @@ extern void ___OpenCLGridSampleCreator__OpType_GridSample__IMAGE__(); #ifdef MNN_SUPPORT_TRANSFORMER_FUSE extern void ___OpenCLAttentionBufCreator__OpType_Attention__BUFFER__(); +extern void ___OpenCLSelfAttentionBufCreator__OpType_FmhaV2__BUFFER__(); +extern void ___OpenCLGroupNormBufCreator__OpType_GroupNorm__BUFFER__(); +extern void ___OpenCLSplitGeluBufCreator__OpType_SplitGeLU__BUFFER__(); #endif void registerOpenCLOps() { ___OpenCLInterp3DBufCreator__OpType_Interp3D__BUFFER__(); @@ -121,6 +124,9 @@ ___OpenCLInterpCreator__OpType_Interp__IMAGE__(); ___OpenCLGridSampleCreator__OpType_GridSample__IMAGE__(); #ifdef MNN_SUPPORT_TRANSFORMER_FUSE ___OpenCLAttentionBufCreator__OpType_Attention__BUFFER__(); +___OpenCLSelfAttentionBufCreator__OpType_FmhaV2__BUFFER__(); +___OpenCLGroupNormBufCreator__OpType_GroupNorm__BUFFER__(); +___OpenCLSplitGeluBufCreator__OpType_SplitGeLU__BUFFER__(); #endif } } diff --git a/source/backend/opencl/core/OpenCLRunningUtils.cpp b/source/backend/opencl/core/OpenCLRunningUtils.cpp index f374b6f73..2ad64aa69 100644 --- a/source/backend/opencl/core/OpenCLRunningUtils.cpp +++ b/source/backend/opencl/core/OpenCLRunningUtils.cpp @@ -95,11 +95,11 @@ std::pair, uint32_t> localWS3DDefault(const std::vectorgetCLTuneLevel() == Wide) { while(lws[2] <= gws[2] || lws[2] <= 6) { @@ -132,22 +132,22 @@ std::pair, uint32_t> localWS3DDefault(const std::vector 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] > 6));//divisible powOfTwo lessThanSix } do { - lws[1]++; + lws[1]<<=1; } while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] > 6));//divisible powOfTwo lessThanSix } do { - lws[2]++; + lws[2]<<=1; } while(((2*gws[2])%lws[2] > 1) && (lws[2] & (lws[2] - 1)) != 0 && (lws[2] <= gws[2]) && (lws[2] > 6));//divisible powOfTwo lessThanSix } } else if(runtime->getCLTuneLevel() == Normal) { - while(lws[2] <= gws[2] && lws[2] <= 6) { + while(lws[2] <= gws[2] && lws[2] <= 8) { lws[1] = 1; while(lws[1] <= gws[1] || lws[1] <= 6) { lws[0] = 1; @@ -177,27 +177,27 @@ std::pair, uint32_t> localWS3DDefault(const std::vector 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] > 6));//divisible powOfTwo lessThanSix } do { - lws[1]++; + lws[1]<<=1; } while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] > 6));//divisible powOfTwo lessThanSix } do { - lws[2]++; + lws[2]<<=1; } while(((2*gws[2])%lws[2] > 1) && (lws[2] & (lws[2] - 1)) != 0 && (lws[2] <= gws[2]) && (lws[2] <= 6));//divisible powOfTwo lessThanSix } } else if(runtime->getCLTuneLevel() == Fast) { - while(lws[2] <= gws[2] && lws[2] <= 6) { + while(lws[2] <= gws[2] && lws[2] <= 8) { lws[1] = 1; - while(lws[1] <= gws[1] && lws[1] <= 6) { + while(lws[1] <= gws[1] && lws[1] <= 8) { lws[0] = 1; - while(lws[0] <= gws[0] && lws[0] <= 6) { - if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[2] <= maxWorkItemSizes[2] && lws[0]*lws[1]*lws[2] <= maxWorkGroupSize) { + while(lws[0] <= gws[0] && lws[0] <= 8) { + if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[2] <= maxWorkItemSizes[2] && lws[0]*lws[1]*lws[2] <= std::min(maxWorkGroupSize, static_cast(64)) && lws[0]*lws[1]*lws[2] >= 16) { cl::Event event; std::vector internalGlobalWS(3, 1); for (size_t i = 0; i < gws.size(); ++i) { @@ -222,17 +222,17 @@ std::pair, uint32_t> localWS3DDefault(const std::vector 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] <= 6));//divisible powOfTwo lessThanSix } do { - lws[1]++; + lws[1]<<=1; } while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] <= 6));//divisible powOfTwo lessThanSix } do { - lws[2]++; + lws[2]<<=1; } while(((2*gws[2])%lws[2] > 1) && (lws[2] & (lws[2] - 1)) != 0 && (lws[2] <= gws[2]) && (lws[2] <= 6));//divisible powOfTwo lessThanSix } @@ -266,7 +266,7 @@ std::pair, uint32_t> localWS3DDefault(const std::vectorgetCLTuneLevel() != None) { - //printf("3dLocalWS %d Insert! gws:%d %d %d, lws:%d %d %d\n", (int)tunedLws.size(), gws[0], gws[1], gws[2], lws_prefer[0], lws_prefer[1], lws_prefer[2]); +// printf("3dLocalWS %d Insert! gws:%d %d %d, lws:%d %d %d\n", (int)tunedLws.size(), gws[0], gws[1], gws[2], lws_prefer[0], lws_prefer[1], lws_prefer[2]); tunedLws.insert(std::make_pair(info, std::make_pair(lws_prefer, min_cost))); } @@ -323,9 +323,9 @@ std::pair, uint32_t> localWS2DDefault(const std::vectorgetCLTuneLevel() == Wide) { while(lws[1] <= gws[1] || lws[1] <= 6) { @@ -355,17 +355,17 @@ std::pair, uint32_t> localWS2DDefault(const std::vector 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] > 6));//divisible powOfTwo lessThanSix } do { - lws[1]++; + lws[1]<<=1; } while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] > 6));//divisible powOfTwo lessThanSix } } else if(runtime->getCLTuneLevel() == Normal) { - while(lws[1] <= gws[1] && lws[1] <= 6) { + while(lws[1] <= gws[1] && lws[1] <= 8) { lws[0] = 1; while(lws[0] <= gws[0] || lws[0] <= 6) { if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize) { @@ -392,20 +392,20 @@ std::pair, uint32_t> localWS2DDefault(const std::vector 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] > 6));//divisible powOfTwo lessThanSix } do { - lws[1]++; + lws[1]<<=1; } while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] <= 6));//divisible powOfTwo lessThanSix } } else if(runtime->getCLTuneLevel() == Fast) { - while(lws[1] <= gws[1] && lws[1] <= 6) { + while(lws[1] <= gws[1] && lws[1] <= 8) { lws[0] = 1; - while(lws[0] <= gws[0] && lws[0] <= 6) { - if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize) { + while(lws[0] <= gws[0] && lws[0] <= 8) { + if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize && lws[0]*lws[1] >= 16) { cl::Event event; std::vector internalGlobalWS(2, 1); for (size_t i = 0; i < gws.size(); ++i) { @@ -429,12 +429,12 @@ std::pair, uint32_t> localWS2DDefault(const std::vector 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] <= 6));//divisible powOfTwo lessThanSix } do { - lws[1]++; + lws[1]<<=1; } while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] <= 6));//divisible powOfTwo lessThanSix } @@ -466,7 +466,7 @@ std::pair, uint32_t> localWS2DDefault(const std::vectorgetCLTuneLevel() != None) { - //printf("2dLocalWS %d Insert! gws:%d %d, lws:%d %d\n", (int)tunedLws.size(), gws[0], gws[1], lws_prefer[0], lws_prefer[1]); +// printf("2dLocalWS %d Insert! gws:%d %d, lws:%d %d\n", (int)tunedLws.size(), gws[0], gws[1], lws_prefer[0], lws_prefer[1]); tunedLws.insert(std::make_pair(info, std::make_pair(lws_prefer, min_cost))); } diff --git a/source/backend/opencl/core/OpenCLRunningUtils.hpp b/source/backend/opencl/core/OpenCLRunningUtils.hpp index eb5090e79..63c3fd7df 100644 --- a/source/backend/opencl/core/OpenCLRunningUtils.hpp +++ b/source/backend/opencl/core/OpenCLRunningUtils.hpp @@ -116,7 +116,8 @@ void runKernel2D(const ::std::shared_ptr &kernel, const std::vector< void runTurnKernelLWS2D(const ::std::shared_ptr &kernel, const std::vector &gws, const std::vector &lws, OpenCLRuntime *runtime); - +std::vector getGemmParams(const std::vector &gemmSize, const std::vector tensorMemory, + OpenCLRuntime *runtime); std::pair, uint32_t> localWS3DDefault(const std::vector &gws, const uint32_t maxWorkGroupSize, OpenCLRuntime *runtime, const std::string &kernelName, const std::shared_ptr &mKernel); diff --git a/source/backend/opencl/core/runtime/OpenCLRuntime.cpp b/source/backend/opencl/core/runtime/OpenCLRuntime.cpp index ee7b149e6..1dde1dcbc 100644 --- a/source/backend/opencl/core/runtime/OpenCLRuntime.cpp +++ b/source/backend/opencl/core/runtime/OpenCLRuntime.cpp @@ -17,10 +17,11 @@ //#define MNN_OPEN_TIME_TRACE #include #include "CLCache_generated.h" +#include "backend/opencl/execution/cl/opencl_source_map.hpp" using namespace CLCache; namespace MNN { -extern const std::map> OpenCLProgramMap; +extern const std::map OpenCLProgramMap; extern std::mutex gCLMutex; bool OpenCLRuntime::getDeviceSupportsExtension(const cl::Device &device, const char *extensionName) { @@ -142,7 +143,6 @@ OpenCLRuntime::OpenCLRuntime(const BackendConfig::PrecisionMode precision, const uint32_t num_threads_per_eu = mFirstGPUDevicePtr->getInfo(); uint32_t maxThreadsPerExecutionUnit = num_threads_per_eu > 0 ? num_threads_per_eu : 7; mMaxThreadsPerDevice = maxThreadsPerExecutionUnit * execution_units_count; - mMaxWorkGroupSize = mFirstGPUDevicePtr->getInfo(); } #endif } @@ -230,6 +230,8 @@ OpenCLRuntime::OpenCLRuntime(const BackendConfig::PrecisionMode precision, const mFirstGPUDevicePtr->getInfo(CL_DEVICE_MAX_COMPUTE_UNITS, &mGPUComputeUnits); mFirstGPUDevicePtr->getInfo(CL_DEVICE_MAX_CLOCK_FREQUENCY, &mMaxFreq); mFirstGPUDevicePtr->getInfo(CL_DEVICE_MAX_MEM_ALLOC_SIZE, &mMaxMemAllocSize); + mFirstGPUDevicePtr->getInfo(CL_DEVICE_LOCAL_MEM_SIZE, &mMaxLocalMemSize); + mMaxWorkGroupSize = mFirstGPUDevicePtr->getInfo(); cl_device_fp_config fpConfig; auto success = mFirstGPUDevicePtr->getInfo(CL_DEVICE_HALF_FP_CONFIG, &fpConfig); mIsDeviceSupportedFP16 = CL_SUCCESS == success && fpConfig > 0; @@ -246,7 +248,6 @@ OpenCLRuntime::OpenCLRuntime(const BackendConfig::PrecisionMode precision, const mMemType = IMAGE; } } - mPrecisionLevel = 1; if (mIsDeviceSupportedFP16) { if (precision == BackendConfig::Precision_Low) { @@ -412,10 +413,14 @@ unsigned int OpenCLRuntime::getQueueNum() { return mQueueCount; } +std::map, std::vector>& OpenCLRuntime::tunedGemmParamsMap() { + return mTunedGemmParams; +} + std::map>, std::pair, uint32_t>>& OpenCLRuntime::tunedLwsMap() { return mTunedLws; } - + std::map, std::pair, uint32_t>>>>& OpenCLRuntime::getTuneLwsMap() { return mTuneLws; } @@ -503,7 +508,7 @@ bool OpenCLRuntime::loadProgram(const std::string &programName, cl::Program *pro auto it_source = OpenCLProgramMap.find(programName); if (it_source != OpenCLProgramMap.end()) { cl::Program::Sources sources; - std::string source(it_source->second.begin(), it_source->second.end()); + std::string source(it_source->second); sources.push_back(source); *program = cl::Program(context(), sources); return true; @@ -605,12 +610,14 @@ std::shared_ptr OpenCLRuntime::buildKernelWithCache(const std::strin buildOptionsStr += " -DOUTPUT_TYPE4=char4"; buildOptionsStr += " -DOUTPUT_TYPE16=char16"; buildOptionsStr += " -DCONVERT_OUTPUT4=convert_char4"; + buildOptionsStr += " -DCONVERT_OUTPUT16=convert_char16"; buildOptionsStr += " -DWI_DATA=write_imagei"; } else if(output->getType().bits == 32){ buildOptionsStr += " -DOUTPUT_TYPE=int"; buildOptionsStr += " -DOUTPUT_TYPE4=int4"; buildOptionsStr += " -DOUTPUT_TYPE16=int16"; buildOptionsStr += " -DCONVERT_OUTPUT4=convert_int4"; + buildOptionsStr += " -DCONVERT_OUTPUT16=convert_int16"; buildOptionsStr += " -DWI_DATA=write_imagei"; } else { MNN_PRINT("opencl input datatype not support, bit:%d\n", output->getType().bits); @@ -625,12 +632,14 @@ std::shared_ptr OpenCLRuntime::buildKernelWithCache(const std::strin buildOptionsStr += " -DOUTPUT_TYPE4=uchar4"; buildOptionsStr += " -DOUTPUT_TYPE16=uchar16"; buildOptionsStr += " -DCONVERT_OUTPUT4=convert_uchar4"; + buildOptionsStr += " -DCONVERT_OUTPUT16=convert_uchar16"; buildOptionsStr += " -DWI_DATA=write_imageui"; } else if(output->getType().bits == 32){ buildOptionsStr += " -DOUTPUT_TYPE=uint"; buildOptionsStr += " -DOUTPUT_TYPE4=uint4"; buildOptionsStr += " -DOUTPUT_TYPE16=uint16"; buildOptionsStr += " -DCONVERT_OUTPUT4=convert_uint4"; + buildOptionsStr += " -DCONVERT_OUTPUT16=convert_uint16"; buildOptionsStr += " -DWI_DATA=write_imageui"; } else { MNN_PRINT("opencl input datatype not support, bit:%d\n", output->getType().bits); @@ -681,6 +690,7 @@ std::shared_ptr OpenCLRuntime::buildKernelWithCache(const std::strin auto status = this->buildProgram(buildOptionsStr, &program); if (!status) { FUNC_PRINT_ALL(programName.c_str(), s); + return nullptr; } ProgramWithKernel pwk; pwk.program = program; @@ -699,7 +709,10 @@ std::shared_ptr OpenCLRuntime::buildKernelWithCache(const std::strin if (kiter->second.recycle.empty()) { cl_int res; kernel.reset(new cl::Kernel(program, kernelName.c_str(), &res)); - MNN_CHECK_CL_SUCCESS(res, "getKernel"); + if(res != CL_SUCCESS) { + MNN_ERROR("getKernel: %s error, res:%d\n", kernelName.c_str(), res); + return nullptr; + } if (firstCreate) { kernel->getWorkGroupInfo(*mFirstGPUDevicePtr, CL_KERNEL_WORK_GROUP_SIZE, &kiter->second.maxWorkGroupSize); } @@ -767,6 +780,9 @@ std::vector OpenCLRuntime::getMaxWorkItemSizes() { return mMaxWorkIterms; } +uint64_t OpenCLRuntime::getMaxLocalMem() const { + return mMaxLocalMemSize; +} double OpenCLRuntime::getCostTime(const cl::Event *event){ //cl_int res = mCommandQueuePtr->finish(); cl_int res = event->wait(); @@ -803,6 +819,18 @@ std::pair OpenCLRuntime::makeCache(void* tuneInfo) { for (auto& iter : mBuildProgramMap) { std::unique_ptr pro(new ShaderT); auto program = iter.second.program; + auto bufferSize = iter.second.BufferSize; + // Only use first one + pro->program = std::get<0>(iter.first); + pro->buildInfo = std::get<1>(iter.first); + + //MNN_PRINT("%s - %s - %s\n", pro->program.c_str(), pro->kernel.c_str(), pro->buildInfo.c_str()); + if(bufferSize != 0){ + pro->buffer.resize(bufferSize); + ::memcpy(pro->buffer.data(), iter.second.Buffer.get(), bufferSize); + cache->programs.emplace_back(std::move(pro)); + continue; + } auto devicesNumber = program.getInfo(); auto devices = program.getInfo(); auto binSizes = program.getInfo(); @@ -810,11 +838,6 @@ std::pair OpenCLRuntime::makeCache(void* tuneInfo) { MNN_ERROR("Can't load binary, binarySize:%lu, deviceSize:%lu\n", binSizes.size(), devices.size()); continue; } - // Only use first one - pro->program = std::get<0>(iter.first); - pro->buildInfo = std::get<1>(iter.first); - - //MNN_PRINT("%s - %s - %s\n", pro->program.c_str(), pro->kernel.c_str(), pro->buildInfo.c_str()); pro->buffer.resize(binSizes[0]); auto proRaw = program.get(); @@ -832,6 +855,14 @@ std::pair OpenCLRuntime::makeCache(void* tuneInfo) { cache->tunings.emplace_back(std::move(tuning)); } + // Get All GemmInfo cache + for (auto& iter : mTunedGemmParams) { + std::unique_ptr tuning(new GemmInfoT); + tuning->gemmSize = iter.first; + tuning->paramInfo = iter.second; + cache->gemm.emplace_back(std::move(tuning)); + } + flatbuffers::FlatBufferBuilder builder; auto lastOffset = Cache::Pack(builder, cache.get()); builder.Finish(lastOffset); @@ -842,17 +873,13 @@ std::pair OpenCLRuntime::makeCache(void* tuneInfo) { bool OpenCLRuntime::setCache(std::pair cache) { if (nullptr == cache.first) { - mCacheOutside = nullptr; - mCacheOutsideSize = 0; mBuffer.clear(); return true; } - - mCacheOutsideSize = cache.second; - mCacheOutside = cache.first; + auto cacheBuffer = GetCache(cache.first); - if(nullptr == cacheBuffer->programs() && nullptr == cacheBuffer->tunings()) { + if(nullptr == cacheBuffer->programs() && nullptr == cacheBuffer->tunings() && nullptr == cacheBuffer->gemm()) { return false; } @@ -885,6 +912,9 @@ bool OpenCLRuntime::setCache(std::pair cache) { } ProgramWithKernel pwk; pwk.program = pro; + pwk.Buffer.reset(new char[bufferSize]); + pwk.BufferSize = bufferSize; + ::memcpy(pwk.Buffer.get(), buffer, bufferSize); mBuildProgramMap.insert(std::make_pair(std::make_tuple(program, buildinfo), pwk)); } } @@ -911,6 +941,29 @@ bool OpenCLRuntime::setCache(std::pair cache) { mTuneLws[tun->key()->str()].push_back(std::make_pair(glo, std::make_pair(loc, cost))); } } + + // Load Gemm Info + if (nullptr != cacheBuffer->gemm()) { + auto tuningInfo = cacheBuffer->gemm(); + for (int i=0; isize(); ++i) { + auto tun = tuningInfo->GetAs(i); + if (nullptr == tun->gemmSize() || nullptr == tun->paramInfo()) { + MNN_ERROR("Error tunning gemm info\n"); + return false; + } + MNN_ASSERT(tun->gemmSize()->size() == 6); + std::vector info(tun->gemmSize()->size()); + for (int v=0; vgemmSize()->data()[v]; + } + MNN_ASSERT(tun->paramInfo()->size() == 16); + std::vector params(tun->paramInfo()->size()); + for (int v=0; vparamInfo()->data()[v]; + } + mTunedGemmParams.insert(std::make_pair(info, params)); + } + } return true; } @@ -920,7 +973,7 @@ void OpenCLRuntime::printEventTime(){ return; } int raster_num = 0, raster_time = 0; - unsigned int conv_time = 0, loop_bg_time = 0, loop_bg_gemm_time = 0; + unsigned int conv_time = 0, loop_bg_time = 0, loop_bg_gemm_time = 0, loop_softmax_time = 0, ori_softmax_time = 0; unsigned int conv_gemm2_buf_time = 0, conv_gemm1_buf_time = 0; unsigned int conv_1x1_buf_time = 0, conv_ori_buf_time = 0, wino_gemm_time = 0; @@ -954,6 +1007,12 @@ void OpenCLRuntime::printEventTime(){ if((mEvents[i].first.length() >= 20 && mEvents[i].first.substr(0, 20) == "While-gemm-batchgemm")) { loop_bg_gemm_time += kernel_time; } + if((mEvents[i].first.length() >= 18 && mEvents[i].first.substr(0, 18) == "While-gemm-softmax")) { + loop_softmax_time += kernel_time; + } + if((mEvents[i].first.length() >= 7 && mEvents[i].first.substr(0, 7) == "Softmax")) { + ori_softmax_time += kernel_time; + } if((mEvents[i].first.length() >= 23 && mEvents[i].first.substr(0, 23) == "Conv-winograd-batchgemm")) { wino_gemm_time += kernel_time; conv_time += kernel_time; @@ -978,7 +1037,7 @@ void OpenCLRuntime::printEventTime(){ MNN_PRINT("kernel time = %d us %s\n", kernels[i].second, kernels[i].first.c_str()); } mEvents.clear(); - MNN_PRINT("total kernel time = %d us, conv time = %d us (gemm2:%d us, gemm1:%d us, 1x1:%d us, ori:%d us, wino: %d us, other: %d us), while gemm time = %d us (core gemm time: %d us)\n", mKernelTime, conv_time, conv_gemm2_buf_time, conv_gemm1_buf_time, conv_1x1_buf_time, conv_ori_buf_time, wino_gemm_time, conv_time-conv_gemm2_buf_time-conv_gemm1_buf_time-conv_1x1_buf_time-conv_ori_buf_time-wino_gemm_time, loop_bg_time, loop_bg_gemm_time); + MNN_PRINT("total kernel time = %d us, conv time = %d us (gemm2:%d us, gemm1:%d us, 1x1:%d us, ori:%d us, wino: %d us, other: %d us), while gemm time = %d us (core gemm time: %d us, softmax:%d us), ori softmax: %d us\n", mKernelTime, conv_time, conv_gemm2_buf_time, conv_gemm1_buf_time, conv_1x1_buf_time, conv_ori_buf_time, wino_gemm_time, conv_time-conv_gemm2_buf_time-conv_gemm1_buf_time-conv_1x1_buf_time-conv_ori_buf_time-wino_gemm_time, loop_bg_time, loop_bg_gemm_time, loop_softmax_time, ori_softmax_time); #endif } } // namespace MNN diff --git a/source/backend/opencl/core/runtime/OpenCLRuntime.hpp b/source/backend/opencl/core/runtime/OpenCLRuntime.hpp index 3e208e806..13f40a6c6 100644 --- a/source/backend/opencl/core/runtime/OpenCLRuntime.hpp +++ b/source/backend/opencl/core/runtime/OpenCLRuntime.hpp @@ -139,6 +139,9 @@ class OpenCLRuntime { unsigned int getQueueNum(); unsigned int mKernelTime = 0; + + + std::map, std::vector>& tunedGemmParamsMap(); std::map>, std::pair, uint32_t>>& tunedLwsMap(); @@ -182,6 +185,8 @@ class OpenCLRuntime { struct ProgramWithKernel { cl::Program program; std::map kernels; + std::shared_ptr Buffer; + int BufferSize = 0; }; cl::CommandQueue* mCurrentCommandQueue; std::map, ProgramWithKernel> mBuildProgramMap; @@ -223,11 +228,10 @@ class OpenCLRuntime { double mStartNanos; double mStopNanos; + std::map, std::vector> mTunedGemmParams; std::map>, std::pair, uint32_t>> mTunedLws; std::map, std::pair, uint32_t>>>> mTuneLws; std::vector mBuffer; - const void* mCacheOutside = nullptr; - size_t mCacheOutsideSize = 0; }; } // namespace MNN diff --git a/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp b/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp index 3ff74740f..2382a7081 100644 --- a/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/AttentionBufExecution.cpp @@ -7,6 +7,7 @@ // #ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE #include "backend/opencl/execution/buffer/AttentionBufExecution.hpp" @@ -25,7 +26,7 @@ void AttentionBufImpl::allocKVCache() { return; } mMaxLength = mPastLength + mExpandChunk; - size_t buffer_size = UP_DIV(mMaxLength, 4) * mNumHead * mHeadDim * 4 * mByte; + size_t buffer_size = UP_DIV(mMaxLength, 4) * mKvNumHead * mHeadDim * 4 * mByte; // past_key: [1, numhead, headdim, maxlen] mPastKey.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); // past_value: [1, numhead, maxlen, headdim] @@ -36,9 +37,10 @@ void AttentionBufImpl::reallocKVCache() { if (!mKVCache || mPastLength < mMaxLength) { return; } - size_t old_size = mNumHead * UP_DIV(mMaxLength, 4) * mHeadDim * 4 * mByte; + + size_t old_size = mKvNumHead * UP_DIV(mMaxLength, 4) * mHeadDim * 4 * mByte; mMaxLength = mPastLength + mExpandChunk; - size_t buffer_size = UP_DIV(mMaxLength, 4) * mNumHead * mHeadDim * 4 * mByte; + size_t buffer_size = UP_DIV(mMaxLength, 4) * mKvNumHead * mHeadDim * 4 * mByte; // past_key: [1, numhead, headdim, maxlen] auto new_key = new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size); // past_value: [1, numhead, maxlen, headdim] @@ -69,25 +71,25 @@ void AttentionBufImpl::reallocKVCache() { mPastKey.reset(new_key); mPastValue.reset(new_value); - size_t temp_size = UP_DIV(mMaxLength, 4) * mNumHead * 4 * mByte; - mTempQK.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, temp_size)); - mTempSoftMax.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, temp_size)); - + mTempQK.reset(Tensor::createDevice({UP_DIV(mMaxLength, 4) * mNumHead * 4})); + mTempSoftMax.reset(Tensor::createDevice({UP_DIV(mMaxLength, 4) * mNumHead * 4})); + mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::STATIC); + mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::STATIC); // reset memory for args if(mOpenCLBackend->isUseRecordQueue()){ - mQkUpdateInfo.update_kernel_args[1].arg_value = &(*(mTempQK.get()))(); + mQkUpdateInfo.update_kernel_args[1].arg_value = &openCLBuffer(mTempQK.get())(); mQkUpdateInfo.update_kernel_args[2].arg_value = &(*(mPastKey.get()))(); - mSoftMaxUpdateInfo.update_kernel_args[0].arg_value = &(*(mTempQK.get()))(); - mSoftMaxUpdateInfo.update_kernel_args[1].arg_value = &(*(mTempSoftMax.get()))(); - mQkvUpdateInfo.update_kernel_args[0].arg_value = &(*(mTempSoftMax.get()))(); + mSoftMaxUpdateInfo.update_kernel_args[0].arg_value = &openCLBuffer(mTempQK.get())(); + mSoftMaxUpdateInfo.update_kernel_args[1].arg_value = &openCLBuffer(mTempSoftMax.get())(); + mQkvUpdateInfo.update_kernel_args[0].arg_value = &openCLBuffer(mTempSoftMax.get())(); mQkvUpdateInfo.update_kernel_args[1].arg_value = &(*(mPastValue.get()))(); }else{ cl_int ret = CL_SUCCESS; - ret |= mKernel_qk->get().setArg(5, *mTempQK.get()); + ret |= mKernel_qk->get().setArg(5, openCLBuffer(mTempQK.get())); ret |= mKernel_qk->get().setArg(6, *mPastKey.get()); - ret |= mKernel_softmax->get().setArg(3, *mTempQK.get()); - ret |= mKernel_softmax->get().setArg(4, *mTempSoftMax.get()); - ret |= mKernel_qkv->get().setArg(3, *mTempSoftMax.get()); + ret |= mKernel_softmax->get().setArg(3, openCLBuffer(mTempQK.get())); + ret |= mKernel_softmax->get().setArg(4, openCLBuffer(mTempSoftMax.get())); + ret |= mKernel_qkv->get().setArg(3, openCLBuffer(mTempSoftMax.get())); ret |= mKernel_qkv->get().setArg(6, *mPastValue.get()); MNN_CHECK_CL_SUCCESS(ret, "reset memory arg for AttentionBufExecution"); } @@ -125,6 +127,8 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorshape()[2]; + int group_size = mNumHead / mKvNumHead; mHeadDim = shape[3]; mScale = 1.0 / sqrt(mHeadDim); mIsDecode = seq_len == 1; @@ -142,14 +146,14 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorgetOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); - mTempSoftMax.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); + mTempQK.reset(Tensor::createDevice({UP_DIV(mMaxLength, 4) * mNumHead * 4})); + mTempSoftMax.reset(Tensor::createDevice({UP_DIV(mMaxLength, 4) * mNumHead * 4})); } else { - size_t buffer_size = UP_DIV(mPastLength, 4) * mPastLength * mNumHead * 4 * mByte; - mTempQK.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); - mTempSoftMax.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); + mTempQK.reset(Tensor::createDevice({UP_DIV(mPastLength, 4) * mPastLength * mNumHead * 4})); + mTempSoftMax.reset(Tensor::createDevice({UP_DIV(mPastLength, 4) * mPastLength * mNumHead * 4})); } + mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::DYNAMIC); // query * key -> div -> select { @@ -163,6 +167,7 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorgetType() == halide_type_of()){ buildOption.emplace("-DADD_MASK"); } + buildOption.emplace("-DNUMHEAD_GROUP_SIZE=" + std::to_string(group_size)); mKernel_qk = runtime->buildKernel("attention_buf", "matmul_qk_div_mask", buildOption, inputs[0], outputs[0]); mGlobalWorkSizeQk = {static_cast(UP_DIV(seq_len, 4)), static_cast(mNumHead), static_cast(UP_DIV(mKv_seq_len, 4))}; auto maxWorkGroupSize = static_cast(runtime->getMaxWorkGroupSize(mKernel_qk)); @@ -175,13 +180,14 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorget().setArg(index++, mGlobalWorkSizeQk2); ret |= mKernel_qk->get().setArg(index++, openCLBuffer(query)); ret |= mKernel_qk->get().setArg(index++, openCLBuffer(key)); - ret |= mKernel_qk->get().setArg(index++, *mTempQK.get()); + ret |= mKernel_qk->get().setArg(index++, openCLBuffer(mTempQK.get())); ret |= mKernel_qk->get().setArg(index++, *mPastKey.get()); ret |= mKernel_qk->get().setArg(index++, openCLBuffer(mask)); ret |= mKernel_qk->get().setArg(index++, mScale); ret |= mKernel_qk->get().setArg(index++, seq_len); ret |= mKernel_qk->get().setArg(index++, mKv_seq_len); ret |= mKernel_qk->get().setArg(index++, mNumHead); + ret |= mKernel_qk->get().setArg(index++, mKvNumHead); ret |= mKernel_qk->get().setArg(index++, mHeadDim); MNN_CHECK_CL_SUCCESS(ret, "setArg matmul_qk_div_mask"); @@ -190,7 +196,7 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorget().setArg(index++, mGlobalWorkSizeSoftMax[0]); ret |= mKernel_softmax->get().setArg(index++, mGlobalWorkSizeSoftMax[1]); ret |= mKernel_softmax->get().setArg(index++, mGlobalWorkSizeSoftMax[2]); - ret |= mKernel_softmax->get().setArg(index++, *mTempQK.get()); - ret |= mKernel_softmax->get().setArg(index++, *mTempSoftMax.get()); + ret |= mKernel_softmax->get().setArg(index++, openCLBuffer(mTempQK.get())); + ret |= mKernel_softmax->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); ret |= mKernel_softmax->get().setArg(index++, mSoftMaxRemainChannels); ret |= mKernel_softmax->get().setArg(index++, mSoftmaxShape); MNN_CHECK_CL_SUCCESS(ret, "setArg softmax"); @@ -244,8 +250,8 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vector(runtime->getMaxWorkGroupSize(mKernel_qkv)); mGlobalWorkSizeQkv = {static_cast(UP_DIV(seq_len, 4)), static_cast(mNumHead), static_cast(UP_DIV(mHeadDim, 4))}; @@ -270,13 +277,14 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorget().setArg(index++, mGlobalWorkSizeQkv[0]); ret |= mKernel_qkv->get().setArg(index++, mGlobalWorkSizeQkv[1]); ret |= mKernel_qkv->get().setArg(index++, mGlobalWorkSizeQkv[2]); - ret |= mKernel_qkv->get().setArg(index++, *mTempSoftMax.get()); + ret |= mKernel_qkv->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); ret |= mKernel_qkv->get().setArg(index++, openCLBuffer(value)); ret |= mKernel_qkv->get().setArg(index++, openCLBuffer(outputs[0])); ret |= mKernel_qkv->get().setArg(index++, *mPastValue.get()); ret |= mKernel_qkv->get().setArg(index++, seq_len); ret |= mKernel_qkv->get().setArg(index++, mKv_seq_len); ret |= mKernel_qkv->get().setArg(index++, mNumHead); + ret |= mKernel_qkv->get().setArg(index++, mKvNumHead); ret |= mKernel_qkv->get().setArg(index++, mHeadDim); MNN_CHECK_CL_SUCCESS(ret, "setArg matmul_qkv"); @@ -285,7 +293,7 @@ ErrorCode AttentionBufImpl::onResize(Backend *backend, const std::vectorendRecord(mRecording); + + mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::DYNAMIC); return NO_ERROR; } @@ -414,5 +425,6 @@ REGISTER_OPENCL_OP_CREATOR(AttentionBufCreator, OpType_Attention, BUFFER); } // namespace OpenCL } // namespace MNN +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ #endif/* MNN_OPENCL_BUFFER_CLOSED */ diff --git a/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp b/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp index 20ee66ec6..9de3796d9 100644 --- a/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp +++ b/source/backend/opencl/execution/buffer/AttentionBufExecution.hpp @@ -7,6 +7,7 @@ // #ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE #ifndef AttentionBufExecution_hpp #define AttentionBufExecution_hpp @@ -36,12 +37,13 @@ class AttentionBufImpl { void reallocKVCache(); bool mKVCache; float mScale; - const int mExpandChunk = 64; + const int mExpandChunk = 2048; bool mIsDecode = false; bool mIsFirstDecode = true; int mPastLength = 0, mMaxLength = 0, mKv_seq_len = 0, mSoftMaxRemainChannels = 0; - std::shared_ptr mPastKey, mPastValue, mTempQK, mTempSoftMax; - int mNumHead = 0, mHeadDim = 0, mValueH = 0; + std::shared_ptr mPastKey, mPastValue; + std::shared_ptr mTempQK, mTempSoftMax; + int mNumHead = 0, mKvNumHead = 0, mHeadDim = 0, mValueH = 0; std::shared_ptr mKernel_qk; std::shared_ptr mKernel_softmax; std::shared_ptr mKernel_qkv; @@ -80,4 +82,5 @@ class AttentionBufExecution : public CommonExecution { } // namespace OpenCL } // namespace MNN #endif /* AttentionBufExecution_hpp */ +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ #endif /* MNN_OPENCL_BUFFER_CLOSED */ diff --git a/source/backend/opencl/execution/buffer/BinaryBufExecution.cpp b/source/backend/opencl/execution/buffer/BinaryBufExecution.cpp index 35c98970c..47b75864f 100644 --- a/source/backend/opencl/execution/buffer/BinaryBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/BinaryBufExecution.cpp @@ -400,7 +400,7 @@ class BinaryBufCreator : public OpenCLBackend::Creator { case BinaryOpOperation_NOTEQUAL: return new BinaryBufExecution(inputs, "convert_float4(-isnotequal(in0,in1))", op, backend); case BinaryOpOperation_MOD: - return new BinaryBufExecution(inputs, "fmod(in0,in1)", op, backend); + return new BinaryBufExecution(inputs, "in0-floor(sign(in1)*in0/(fabs(in1)>(float4)((float)0.0000001)?fabs(in1):(float4)((float)0.0000001)))*in1", op, backend); default: break; } diff --git a/source/backend/opencl/execution/buffer/ConvBufExecution.cpp b/source/backend/opencl/execution/buffer/ConvBufExecution.cpp index fc3778133..d0fdc0cda 100644 --- a/source/backend/opencl/execution/buffer/ConvBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/ConvBufExecution.cpp @@ -18,192 +18,7 @@ namespace MNN { namespace OpenCL { -std::pair, uint32_t> ConvBufCommonExecution::gws2dLwsTune(const std::shared_ptr &kernelW, const std::vector &gws, const std::string &kernelName, const uint32_t maxWorkGroupSize) { - MNN_ASSERT(gws.size() == 2); - auto kernel = kernelW->get(); - auto runtime = mOpenCLBackend->getOpenCLRuntime(); - auto maxWorkItemSizes = runtime->getMaxWorkItemSizes(); - MNN_ASSERT(maxWorkItemSizes.size() >= 2); - - auto& tunedLws = runtime->tunedLwsMap(); - auto& tuneLws = runtime->getTuneLwsMap(); - std::pair> info = std::make_pair(kernelName, gws); - if (tunedLws.find(info) != tunedLws.end()) { - //printf("ConvBuf2dGeneralLocalWS Found! gws:%d %d lws:%d %d\n", gws[0], gws[1], tunedLws[info][0], tunedLws[info][1]); - return tunedLws[info]; - } - std::pair, uint32_t> tuneLwsRes; - if(localWSTune(tuneLws, gws, kernelName, tuneLwsRes)){ - return tuneLwsRes; - } - - std::vector lws(3, 1); - std::vector lws_prefer(3, 1); - uint32_t min_cost = UINT_MAX; - - if(runtime->getCLTuneLevel() == Heavy) { - while(lws[1] <= gws[1] || lws[1] <= 6) { - lws[0] = 1; - while(lws[0] <= gws[0] || lws[0] <= 6) { - if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize) { - cl::Event event; - std::vector internalGlobalWS(2, 1); - for (size_t i = 0; i < gws.size(); ++i) { - internalGlobalWS[i] = ROUND_UP(gws[i], std::max((uint32_t)1, lws[i])); - } - cl_int res = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueNDRangeKernel( - kernel, cl::NullRange, - cl::NDRange(internalGlobalWS[0], internalGlobalWS[1]), - cl::NDRange(lws[0], lws[1]), - nullptr, &event); - MNN_CHECK_CL_SUCCESS(res, kernelName.c_str()); - - int cost_time = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event); - if(cost_time < min_cost) { - min_cost = cost_time; - lws_prefer[0] = lws[0]; - lws_prefer[1] = lws[1]; - } - } - lws[0]<<=1; - } - lws[1]<<=1; - } - } else if(runtime->getCLTuneLevel() == Wide) { - while(lws[1] <= gws[1] || lws[1] <= 6) { - lws[0] = 1; - while(lws[0] <= gws[0] || lws[0] <= 6) { - if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize) { - cl::Event event; - std::vector internalGlobalWS(2, 1); - for (size_t i = 0; i < gws.size(); ++i) { - internalGlobalWS[i] = ROUND_UP(gws[i], std::max((uint32_t)1, lws[i])); - } - cl_int res = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueNDRangeKernel( - kernel, cl::NullRange, - cl::NDRange(internalGlobalWS[0], internalGlobalWS[1]), - cl::NDRange(lws[0], lws[1]), - nullptr, &event); - MNN_CHECK_CL_SUCCESS(res, kernelName.c_str()); - - int cost_time = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event); - if(cost_time < min_cost) { - min_cost = cost_time; - lws_prefer[0] = lws[0]; - lws_prefer[1] = lws[1]; - } - } - do { - lws[0]<<=1; - } - while(((2*gws[0])%lws[0] > 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] > 6));//divisible powOfTwo lessThanSix - } - do { - lws[1]<<=1; - } - while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] > 6));//divisible powOfTwo lessThanSix - } - } else if(runtime->getCLTuneLevel() == Normal) { - while(lws[1] <= gws[1] && lws[1] <= 6) { - lws[0] = 1; - while(lws[0] <= gws[0] || lws[0] <= 6) { - if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize) { - cl::Event event; - std::vector internalGlobalWS(2, 1); - for (size_t i = 0; i < gws.size(); ++i) { - internalGlobalWS[i] = ROUND_UP(gws[i], std::max((uint32_t)1, lws[i])); - } - cl_int res = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueNDRangeKernel( - kernel, cl::NullRange, - cl::NDRange(internalGlobalWS[0], internalGlobalWS[1]), - cl::NDRange(lws[0], lws[1]), - nullptr, &event); - MNN_CHECK_CL_SUCCESS(res, kernelName.c_str()); - - int cost_time = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event); - if(cost_time < min_cost) { - min_cost = cost_time; - lws_prefer[0] = lws[0]; - lws_prefer[1] = lws[1]; - } - } - do { - lws[0]<<=1; - } - while(((2*gws[0])%lws[0] > 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] > 6));//divisible powOfTwo lessThanSix - } - do { - lws[1]<<=1; - } - while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] <= 6));//divisible powOfTwo lessThanSix - } - } else if(runtime->getCLTuneLevel() == Fast) { - while(lws[1] <= gws[1] && lws[1] <= 6) { - lws[0] = 1; - while(lws[0] <= gws[0] && lws[0] <= 6) { - if(lws[0] <= maxWorkItemSizes[0] && lws[1] <= maxWorkItemSizes[1] && lws[0]*lws[1] <= maxWorkGroupSize) { - cl::Event event; - std::vector internalGlobalWS(2, 1); - for (size_t i = 0; i < gws.size(); ++i) { - internalGlobalWS[i] = ROUND_UP(gws[i], std::max((uint32_t)1, lws[i])); - } - cl_int res = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueNDRangeKernel( - kernel, cl::NullRange, - cl::NDRange(internalGlobalWS[0], internalGlobalWS[1]), - cl::NDRange(lws[0], lws[1]), - nullptr, &event); - MNN_CHECK_CL_SUCCESS(res, kernelName.c_str()); - - int cost_time = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event); - if(cost_time < min_cost) { - min_cost = cost_time; - lws_prefer[0] = lws[0]; - lws_prefer[1] = lws[1]; - } - } - do { - lws[0]<<=1; - } - while(((2*gws[0])%lws[0] > 1) && (lws[0] & (lws[0] - 1)) != 0 && (lws[0] <= gws[0]) && (lws[0] <= 6));//divisible powOfTwo lessThanSix - } - do { - lws[1]<<=1; - } - while(((2*gws[1])%lws[1] > 1) && (lws[1] & (lws[1] - 1)) != 0 && (lws[1] <= gws[1]) && (lws[1] <= 6));//divisible powOfTwo lessThanSix - } - } else if(runtime->getCLTuneLevel() == None) { - // define not tune method to choose lws - if(runtime->getGpuMemType() == GpuMemObject::IMAGE) { - lws_prefer[0] = 8; - lws_prefer[1] = 4; - } else { - lws_prefer[0] = 0; - lws_prefer[1] = 0; - } - cl::Event event; - std::vector internalGlobalWS(2, 1); - for (size_t i = 0; i < gws.size(); ++i) { - internalGlobalWS[i] = ROUND_UP(gws[i], std::max((uint32_t)1, lws_prefer[i])); - } - cl_int res = CL_SUCCESS; - if(lws_prefer[0] == 0 || lws_prefer[1] == 0){ - res = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueNDRangeKernel( - kernel, cl::NullRange, cl::NDRange(internalGlobalWS[0], internalGlobalWS[1]), cl::NullRange, nullptr, &event); - }else{ - res = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueNDRangeKernel( - kernel, cl::NullRange, cl::NDRange(internalGlobalWS[0], internalGlobalWS[1]), cl::NDRange(lws_prefer[0], lws_prefer[1]), nullptr, &event); - } - MNN_CHECK_CL_SUCCESS(res, kernelName.c_str()); - min_cost = (int)mOpenCLBackend->getOpenCLRuntime()->getCostTime(&event); - } - - if (tunedLws.find(info) == tunedLws.end() && runtime->getCLTuneLevel() != None) { - //printf("ConvBuf2dGeneralLocalWS %d Insert! gws:%d %d, lws:%d %d, time:%dus\n", (int)tunedLws.size(), gws[0], gws[1], lws_prefer[0], lws_prefer[1], min_cost); - tunedLws.insert(std::make_pair(info, std::make_pair(lws_prefer, min_cost))); - } - return std::make_pair(lws_prefer, min_cost); -} ConvBufCommonExecution::ConvBufCommonExecution(Backend *backend) { mOpenCLBackend = static_cast(backend); } @@ -353,7 +168,7 @@ ConvBufExecution::ConvBufExecution(const std::vector &inputs, const st if (mResource->mConvGemmOptLevel > 0) { // Tile Match with mConvGemmOptLevel == 2 int tileK = 32; - int tileN = 128; + int tileN = 32; if(mResource->mConvGemmOptLevel == 1) { tileK = 8; @@ -512,11 +327,10 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const if (mResource->mConvGemmOptLevel == 2) { // set large tile - int tileM = 128; - int tileN = 128; + int tileM = 32; + int tileN = 32; int tileK = 32; - int localM = 32; - int localN = 8; + int M = outputShape.at(0); int N = outputShape.at(3); int K = inputShape.at(3); @@ -555,13 +369,38 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const mPreGlobalWorkSize[0] = ROUND_UP(mPreGlobalWorkSize[0], std::max((uint32_t)1, mPreLocalWorkSize[0])); mPreGlobalWorkSize[1] = ROUND_UP(mPreGlobalWorkSize[1], std::max((uint32_t)1, mPreLocalWorkSize[1])); } - std::set buildOptions = mResource->mBuildOptions; + std::set buildOptions; - // Can't add bias now, for slow speed -// buildOptions.emplace(" -DBIAS"); - - buildOptions.emplace(" -DGEMMK=0 -DKREG=1 -DKWG=32 -DKWI=2 -DMDIMA=32 -DMDIMC=32 -DMWG=128 -DNDIMB=8 -DNDIMC=8 -DNWG=128 -DSA=0 -DSB=0 -DSTRM=0 -DSTRN=1 -DVWM=2 -DVWN=8 -DOUTPUTMN"); - + uint32_t layout = 4; + uint32_t batch = 1; + auto param = getGemmParams({(uint32_t)alignM, (uint32_t)alignN, (uint32_t)alignK, layout, batch}, {openCLBuffer(mConvGemmInpTensor.get()), openCLBuffer(mResource->mFilter.get()), openCLBuffer(mConvGemmOutTensor.get())}, mOpenCLBackend->getOpenCLRuntime()); + + int GEMMK=param[0], KREG=param[1], KWG=param[2], KWI=param[3], MDIMA=param[4], MDIMC=param[5], MWG=param[6], NDIMB=param[7], NDIMC=param[8], NWG=param[9], SA=param[10], SB=param[11], STRM=param[12], STRN=param[13], VWM=param[14], VWN=param[15]; + buildOptions.emplace("-DGEMMK=" + std::to_string(GEMMK)); + buildOptions.emplace("-DKREG=" + std::to_string(KREG)); + buildOptions.emplace("-DKWG=" + std::to_string(KWG)); + buildOptions.emplace("-DKWI=" + std::to_string(KWI)); + buildOptions.emplace("-DMDIMA=" + std::to_string(MDIMA)); + buildOptions.emplace("-DMDIMC=" + std::to_string(MDIMC)); + buildOptions.emplace("-DMWG=" + std::to_string(MWG)); + buildOptions.emplace("-DNDIMB=" + std::to_string(NDIMB)); + buildOptions.emplace("-DNDIMC=" + std::to_string(NDIMC)); + buildOptions.emplace("-DNWG=" + std::to_string(NWG)); + buildOptions.emplace("-DSA=" + std::to_string(SA)); + buildOptions.emplace("-DSB=" + std::to_string(SB)); + buildOptions.emplace("-DSTRM=" + std::to_string(STRM)); + buildOptions.emplace("-DSTRN=" + std::to_string(STRN)); + buildOptions.emplace("-DVWM=" + std::to_string(VWM)); + buildOptions.emplace("-DVWN=" + std::to_string(VWN)); + if(layout >= 4) { + buildOptions.emplace("-DOUTPUTMN"); + } + + tileM = MWG; + tileN = NWG; + int localM = MDIMC; + int localN = NDIMC; + if(mOpenCLBackend->getOpenCLRuntime()->getGpuType() == GpuType::ADRENO) { buildOptions.emplace("-DUSE_CL_MAD=1"); buildOptions.emplace("-DRELAX_WORKGROUP_SIZE=1"); @@ -725,7 +564,7 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const MNN_CHECK_CL_SUCCESS(ret, "setArg Conv1x1Buf Kernel Select"); std::pair, int> retTune; - retTune = gws2dLwsTune(kernel[knl_idx], globalWorkSize[knl_idx], kernelName[knl_idx] + info, maxWorkGroupSize); + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); if(min_cost.first > retTune.second) { min_cost.first = retTune.second; min_cost.second = knl_idx; @@ -819,7 +658,7 @@ ErrorCode ConvBufExecution::onResize(const std::vector &inputs, const MNN_CHECK_CL_SUCCESS(ret, "setArg ConvBuf Kernel Select"); std::pair, int> retTune; - retTune = gws2dLwsTune(kernel[knl_idx], globalWorkSize[knl_idx], kernelName[knl_idx] + info, maxWorkGroupSize); + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); if(min_cost.first > retTune.second) { min_cost.first = retTune.second; @@ -968,11 +807,14 @@ class ConvolutionBufCreator : public OpenCLBackend::Creator { if (((conv2dParams->quanParameter()->type() == 4) || (conv2dParams->quanParameter()->type() == 1) || (conv2dParams->quanParameter()->type() == 2))) { - // Todo: support int4 inputchannel % 4 not equal 4 + if ((1 == conv2dParams->quanParameter()->type() || 2 == conv2dParams->quanParameter()->type()) && conv2dParams->quanParameter()->has_scaleInt()) { + // Don't support IDST-int8 because of error + return nullptr; + } return new ConvBufLowMemoryExecution(inputs, outputs, op, backend); } else { - MNN_ERROR("OpenCL Conv buf low memory init error. For Opencl Backend, only support low memory mode of int8 or int4 dequantization currently.\n"); - MNN_ASSERT(false); + //MNN_ERROR("OpenCL Conv buf low memory init error. For Opencl Backend, only support low memory mode of int8 or int4 dequantization currently.\n"); + return nullptr; } } } diff --git a/source/backend/opencl/execution/buffer/ConvBufExecution.hpp b/source/backend/opencl/execution/buffer/ConvBufExecution.hpp index d5477c603..a1a523ca5 100644 --- a/source/backend/opencl/execution/buffer/ConvBufExecution.hpp +++ b/source/backend/opencl/execution/buffer/ConvBufExecution.hpp @@ -20,14 +20,14 @@ struct ConvBufResource { const Convolution2D *mConv2dParams; std::shared_ptr mKernelBuffer; std::shared_ptr mKernelImage; - std::shared_ptr dequantScale; - std::shared_ptr dequantOffset; + std::shared_ptr dequantScaleOffset; std::shared_ptr mFilter; std::shared_ptr mBias; int mKernelWidth; int mKernelHeight; int mOutputChannel; int mInputChannel; + int mBlockSize; std::vector mStrides{1, 1}; std::vector mDilations{1, 1}; std::set mBuildOptions; @@ -41,6 +41,7 @@ struct ConvBufResource { int mConvGemmOptLevel = 0; std::shared_ptr mRasterExe; bool mUseImage = false; + int mNumQuantBit = 0; }; class ConvBufCommonExecution { @@ -49,7 +50,6 @@ class ConvBufCommonExecution { ConvBufCommonExecution(const Convolution2D *op, Backend *backend); virtual ~ConvBufCommonExecution(); - std::pair, uint32_t> gws2dLwsTune(const std::shared_ptr &kernel, const std::vector &gws, const std::string &kernelName, const uint32_t maxWorkGroupSize); protected: std::shared_ptr mResource; OpenCLBackend *mOpenCLBackend; diff --git a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp index a7b1cc817..36a4afd24 100644 --- a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp +++ b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.cpp @@ -19,143 +19,168 @@ void ConvBufLowMemoryExecution::getInfoFromOpLowMemory(std::shared_ptrquan->type() == 4) { - mNumQuantBit = 8; - } else if (quanCommon->quan->type() == 1 || quanCommon->quan->type() == 2) { - mNumQuantBit = 4; - } else {/* More types to be supported. */} + mResource->mInputChannel = quanCommon->weight.size() / (mResource->mKernelWidth * mResource->mKernelHeight * mResource->mOutputChannel); + // set mResource->mNumQuantBit + if(quanCommon->canUseInt4){ + mResource->mNumQuantBit = 4; + }else{ + mResource->mNumQuantBit = 8; + } // src of alpha in CPU float * dequantAlpha = quanCommon->alpha.get(); + int totalCount = quanCommon->alpha.size(); + if (quanCommon->asymmetric) { + totalCount /= 2; + } int numAlpha = mResource->mOutputChannel; + mResource->mBlockSize = totalCount / numAlpha; // set mDequantScale mDequantOffset - int numAlphaPack = ROUND_UP(numAlpha, 16); - mResource->dequantScale.reset(Tensor::createDevice({numAlphaPack})); - mResource->dequantOffset.reset(Tensor::createDevice({numAlphaPack})); + int numAlphaPack = ROUND_UP(numAlpha, 4); - mOpenCLBackend->onAcquireBuffer(mResource->dequantScale.get(), Backend::STATIC); - mOpenCLBackend->onAcquireBuffer(mResource->dequantOffset.get(), Backend::STATIC); - cl::Buffer &dequantScaleBuffer = openCLBuffer(mResource->dequantScale.get()); - cl::Buffer &dequantOffsetBuffer = openCLBuffer(mResource->dequantOffset.get()); + mResource->dequantScaleOffset.reset(Tensor::createDevice({mResource->mBlockSize, numAlphaPack, 2})); + mOpenCLBackend->onAcquireBuffer(mResource->dequantScaleOffset.get(), Backend::STATIC); + cl::Buffer &dequantScaleOffsetBuffer = openCLBuffer(mResource->dequantScaleOffset.get()); // transfer data from src in cpu to dst in gpu int fpBytes = mOpenCLBackend->fpBytes(); - cl_int resBias, resScale, resOffset; - - - void * dequantScaleBufferMap = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(dequantScaleBuffer, true, CL_MAP_WRITE, 0, numAlphaPack * sizeof(int32_t), nullptr, nullptr, &resScale); - void * dequantOffsetBufferMap = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(dequantOffsetBuffer, true, CL_MAP_WRITE, 0, numAlphaPack * sizeof(int32_t), nullptr, nullptr, &resOffset); - - ::memset(dequantScaleBufferMap, -1, numAlphaPack * sizeof(int32_t)); - ::memset(dequantOffsetBufferMap, 0, numAlphaPack * sizeof(int32_t)); + cl_int resBias, resScaleOffset; - if (dequantScaleBufferMap != nullptr && dequantOffsetBufferMap != nullptr && resScale == CL_SUCCESS && resOffset == CL_SUCCESS) { + int mapSize = mResource->mBlockSize * numAlphaPack * sizeof(int32_t) * 2; + void * dequantScaleOffsetBufferMap = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(dequantScaleOffsetBuffer, true, CL_MAP_WRITE, 0, mapSize, nullptr, nullptr, &resScaleOffset); + // mBlockSize % 4 need equal 0 + if (dequantScaleOffsetBufferMap != nullptr && resScaleOffset == CL_SUCCESS) { if (quanCommon->asymmetric) { for (int i = 0; i < numAlpha; ++i) { - ((float *)dequantOffsetBufferMap)[i] = dequantAlpha[2 * i]; - ((float *)dequantScaleBufferMap)[i] = dequantAlpha[2 * i + 1]; + auto srcZ = dequantAlpha + i * mResource->mBlockSize * 2; + for(int j = 0; j < mResource->mBlockSize; ++j){ + float o = srcZ[2*j+0]; + float s = srcZ[2*j+1]; + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2] = s; + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2 + 1] = o; + } } } else { for (int i = 0; i < numAlpha; ++i) { - ((float *)dequantScaleBufferMap)[i] = dequantAlpha[i]; - ((float *)dequantOffsetBufferMap)[i] = 0.0f; + auto srcZ = dequantAlpha + i * mResource->mBlockSize; + for(int j = 0; j < mResource->mBlockSize; ++j){ + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2] = srcZ[j]; + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2 + 1] = 0.0f; + } } } } else { MNN_ERROR("Map error dequantBufferMap == nullptr \n"); MNN_ASSERT(false); } - mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(dequantScaleBuffer, dequantScaleBufferMap); - mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(dequantOffsetBuffer, dequantOffsetBufferMap); + mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(dequantScaleOffsetBuffer, dequantScaleOffsetBufferMap); // set mFilterDataPtr mFilterDataPtr = (void *)quanCommon->weight.get(); } + +bool ConvBufLowMemoryExecution::convertToQuantWeight1x1Buffer(cl::Buffer input, int pack) { +#ifdef LOG_VERBOSE + MNN_PRINT("start convertToQuantWeight1x1Buffer !\n"); +#endif + auto runtime = mOpenCLBackend->getOpenCLRuntime(); + std::string kernelName = "conv2d_1x1_weight_quant_buffer"; + if(mResource->mUseImage){ + kernelName = "conv2d_1x1_weight_quant_image"; + } + std::set buildOptions; + if (mResource->mNumQuantBit == 8) { + buildOptions.emplace("-DUSE_LOW_BIT_WEIGHT_INT8"); + } else if (mResource->mNumQuantBit == 4){ + // int4 case + buildOptions.emplace("-DUSE_LOW_BIT_WEIGHT_INT4"); + } else {/* More types to be supported. */} + if(mResource->mInputChannel % pack != 0){ + buildOptions.emplace("-DINPUT_CHANNEL_LEAVE"); + } + + mBufferToConv1x1Kernel = runtime->buildKernelWithCache("buffer_convert_quant", kernelName, buildOptions); + auto kernel = mBufferToConv1x1Kernel->get(); + uint32_t gws[2] = {static_cast(UP_DIV(mResource->mInputChannel, pack)), static_cast(mResource->mOutputChannel)}; + + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= kernel.setArg(idx++, gws[0]); + ret |= kernel.setArg(idx++, gws[1]); + ret |= kernel.setArg(idx++, input); + if(mResource->mUseImage){ + ret |= kernel.setArg(idx++, *mResource->mKernelImage.get()); + }else{ + ret |= kernel.setArg(idx++, *mResource->mKernelBuffer.get()); + } + ret |= kernel.setArg(idx++, mResource->mInputChannel); + ret |= kernel.setArg(idx++, mResource->mOutputChannel); + MNN_CHECK_CL_SUCCESS(ret, "setArg convertToQuantWeight1x1Buffer"); + + const uint32_t maxWorkGroupSize = static_cast(runtime->getMaxWorkGroupSize(mBufferToConv1x1Kernel)); + const std::vector lws = {16, std::max((uint32_t)1, maxWorkGroupSize / 16)}; + + cl::Event event; + cl_int res; + + std::vector roundUpGroupWorkSize(lws.size()); + for (size_t i = 0; i < lws.size(); ++i) { + roundUpGroupWorkSize[i] = ROUND_UP(gws[i], lws[i]); + } + + res = runtime->commandQueue().enqueueNDRangeKernel(kernel, cl::NullRange, + cl::NDRange(roundUpGroupWorkSize[0], roundUpGroupWorkSize[1]), + cl::NDRange(lws[0], lws[1]), nullptr, &event); + + event.wait(); + MNN_CHECK_CL_SUCCESS(res, "convertToQuantWeight1x1Buffer"); + +#ifdef LOG_VERBOSE + MNN_PRINT("end convertToQuantWeight1x1Buffer !\n"); +#endif + return true; +} + // set mKernelBuffer for the 1x1 kernels void ConvBufLowMemoryExecution::set1x1WeightLowMemory(int packCout, int packCin, void * filterDataPtr, std::shared_ptr & quanCommon) { cl_int res; std::shared_ptr filterBuffer(Tensor::createDevice({ROUND_UP(mResource->mOutputChannel, packCout), ROUND_UP(mResource->mInputChannel, packCin), mResource->mKernelWidth, mResource->mKernelHeight})); size_t buffer_size = filterBuffer->usize() / sizeof(float); + size_t cpy_size = mResource->mOutputChannel * mResource->mInputChannel * mResource->mKernelWidth * mResource->mKernelHeight * sizeof(char); float *dequantAlpha = quanCommon->alpha.get(); + cl::Buffer filterBufferCL(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size); + void *mapPtr = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(filterBufferCL, true, CL_MAP_WRITE, 0, buffer_size, nullptr, nullptr, &res); + if(mapPtr != nullptr && res == CL_SUCCESS){ + ::memcpy(mapPtr, filterDataPtr, cpy_size); + } else { + MNN_ERROR("set1x1WeightLowMemory: Map error ptrCL == nullptr \n"); + MNN_ASSERT(false); + } + mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(filterBufferCL, mapPtr); // shared part for all cases - if (mNumQuantBit == 8) { + if (mResource->mNumQuantBit == 8) { // int8 case buffer_size *= sizeof(int8_t); - } else if (mNumQuantBit == 4){ + } else if (mResource->mNumQuantBit == 4){ // int4 case buffer_size /= 2; } else {/* More types to be supported. */} // Use Image load weights - void *mapPtr = nullptr; - size_t row_pitch; - size_t slice_pitch; if(UP_DIV(mResource->mInputChannel, packCin) <= 16384 && ROUND_UP(mResource->mOutputChannel, packCout) <= 16384){ mResource->mUseImage = true; } if(mResource->mUseImage) { - if(mNumQuantBit == 4){ + if(mResource->mNumQuantBit == 4){ packCin *= 2; } size_t w = ROUND_UP(mResource->mOutputChannel, packCout); size_t h = UP_DIV(mResource->mInputChannel, packCin); - mResource->mKernelImage.reset(new cl::Image2D(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE, cl::ImageFormat(CL_RGBA, CL_FLOAT), w, h, 0, nullptr, &res)); + mResource->mKernelImage.reset(new cl::Image2D(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE, cl::ImageFormat(CL_RGBA, CL_SIGNED_INT32), w, h, 0, nullptr, &res)); if (nullptr == mResource->mKernelImage.get() || res != CL_SUCCESS) { - MNN_ERROR("Alloc Image %d x %d error, code:%d \n", w, h, res); - } - mapPtr = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapImage(*(mResource->mKernelImage.get()), true, CL_MAP_WRITE, {0, 0, 0}, {w, h, 1}, &row_pitch, &slice_pitch, nullptr, nullptr, &res); - if(mNumQuantBit == 4){ - row_pitch *= 2; + MNN_ERROR("Alloc Image %d x %d error, code:%d \n", (int)w, (int)h, (int)res); } } else{ mResource->mKernelBuffer.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size)); - mapPtr = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(*(mResource->mKernelBuffer.get()), true, CL_MAP_WRITE, 0, buffer_size, nullptr, nullptr, &res); - row_pitch = ROUND_UP(mResource->mOutputChannel, packCout) * packCin; - } - if(mapPtr != nullptr && res == CL_SUCCESS){ - for(int o = 0; o < mResource->mOutputChannel; o++){ - float zero = 0; - if(quanCommon->asymmetric){ - zero = (-dequantAlpha[2 * o + 1])/dequantAlpha[2 * o]; - } - int i = 0; - for(; i < mResource->mInputChannel ; i++){ - int bufferIdx = (i/packCin) * row_pitch + o*packCin + (i%packCin);//(Ci/packCin， Co/packCout * packCout * packCin) - int filterIdx = o*mResource->mInputChannel + i; - if (mNumQuantBit == 8) { - // int8 case - ((int8_t *)mapPtr)[bufferIdx] = (int8_t)(((int8_t *)filterDataPtr)[filterIdx]); - } else if (mNumQuantBit == 4){ - // int4 case - if (bufferIdx % 2 == 0) { - ((uint8_t *)mapPtr)[bufferIdx / 2] += (uint8_t)((((int8_t *)filterDataPtr)[filterIdx] + 8) * 16); - } else { - ((uint8_t *)mapPtr)[bufferIdx / 2] += (uint8_t)(((int8_t *)filterDataPtr)[filterIdx] + 8); - } - } else {/* More types to be supported. */} - } - for(; i < ROUND_UP(mResource->mInputChannel, packCin); i++){ - int bufferIdx = (i/packCin) * row_pitch + o*packCin + (i%packCin);//(Ci/packCin， Co/packCout * packCout * packCin) - if (mNumQuantBit == 8) { - // int8 case - ((int8_t *)mapPtr)[bufferIdx] = (int8_t)(zero); - } else if (mNumQuantBit == 4){ - // int4 case - if (bufferIdx % 2 == 0) { - ((uint8_t *)mapPtr)[bufferIdx / 2] += (uint8_t)((zero + 8) * 16); - } else { - ((uint8_t *)mapPtr)[bufferIdx / 2] += (uint8_t)(zero + 8); - } - } - } - } - } else { - MNN_ERROR("set1x1WeightLowMemory: Map error ptrCL == nullptr \n"); - MNN_ASSERT(false); - } - if(mResource->mUseImage){ - mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(*(mResource->mKernelImage.get()), mapPtr); - } else{ - mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(*(mResource->mKernelBuffer.get()), mapPtr); } + convertToQuantWeight1x1Buffer(filterBufferCL, packCin); } // set mFilter for the general kernels void ConvBufLowMemoryExecution::setGeneralWeightLowMemory(void* filterDataPtr, std::shared_ptr & quanCommon) { @@ -175,31 +200,24 @@ void ConvBufLowMemoryExecution::setGeneralWeightLowMemory(void* filterDataPtr, s ::memset(ptrCL, 0, buffer_size); const int copy_size = mResource->mKernelWidth * mResource->mKernelHeight * sizeof(int8_t); for(int oc=0; ocmOutputChannel; oc++) { - float zero = 0; - if(quanCommon->asymmetric){ - zero = (-dequantAlpha[2 * oc + 1])/dequantAlpha[2 * oc]; - } int ic = 0; for(; icmInputChannel; ic++) { ::memcpy((int8_t *)ptrCL + (oc * ROUND_UP(mResource->mInputChannel, 4) + ic) * mResource->mKernelWidth * mResource->mKernelHeight, ((int8_t *)filterDataPtr) + (oc * mResource->mInputChannel + ic) * mResource->mKernelWidth * mResource->mKernelHeight, copy_size); } - for(; icmInputChannel, 4); ic++) { - ((int8_t *)ptrCL)[(oc * ROUND_UP(mResource->mInputChannel, 4) + ic) * mResource->mKernelWidth * mResource->mKernelHeight] = (int8_t)(zero); - } } } else { MNN_ERROR("setGeneralWeightLowMemory: Map error ptrCL == nullptr \n"); } mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(filterBufferCL, ptrCL); // convert to NC4HW4 - if (mNumQuantBit == 8) { + if (mResource->mNumQuantBit == 8) { // ROUND_UP(IC, 4), UP_DIV(OC, 4) * mKernelWidth * mKernelHeight mResource->mFilter.reset(Tensor::createDevice({1, filterImageShape[1], 1, 4 * filterImageShape[0]})); mOpenCLBackend->onAcquireBuffer(mResource->mFilter.get(), Backend::STATIC); MNN::OpenCL::BufferConvertor bufferConvertor{mOpenCLBackend->getOpenCLRuntime()}; // filterBuffer shape: {OC, ROUND_UP(IC, 4), mKernelWidth, mKernelHeight} - bufferConvertor.convertToNC4HW4Buffer(filterBuffer.get(), MNN::OpenCL::CONV2D_FILTER, mResource->mFilter.get(), false, true, mLowMemoryFlag, mNumQuantBit); - } else if (mNumQuantBit == 4){ + bufferConvertor.convertToNC4HW4Buffer(filterBuffer.get(), MNN::OpenCL::CONV2D_FILTER, mResource->mFilter.get(), false, true, mLowMemoryFlag, mResource->mNumQuantBit); + } else if (mResource->mNumQuantBit == 4){ // ROUND_UP(IC, 4), UP_DIV(OC, 4) * mKernelWidth * mKernelHeight // For int4 case, data stored in mFilter should be uint8_t, // while "Tensor::createDevice" occupies more memory than "Tensor::createDevice". @@ -208,7 +226,7 @@ void ConvBufLowMemoryExecution::setGeneralWeightLowMemory(void* filterDataPtr, s mOpenCLBackend->onAcquireBuffer(mResource->mFilter.get(), Backend::STATIC); MNN::OpenCL::BufferConvertor bufferConvertor{mOpenCLBackend->getOpenCLRuntime()}; // filterBuffer shape: {OC, ROUND_UP(IC, 4), mKernelWidth, mKernelHeight} - bufferConvertor.convertToNC4HW4Buffer(filterBuffer.get(), MNN::OpenCL::CONV2D_FILTER, mResource->mFilter.get(), false, true, mLowMemoryFlag, mNumQuantBit); + bufferConvertor.convertToNC4HW4Buffer(filterBuffer.get(), MNN::OpenCL::CONV2D_FILTER, mResource->mFilter.get(), false, true, mLowMemoryFlag, mResource->mNumQuantBit); } else {/* More types to be supported. */} } else { MNN_ERROR("GetConvParams Error: filterDataPtr == nullptr. \n"); @@ -227,6 +245,7 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor const int inputWidth = inputShape.at(2); const int inputChannels = inputShape.at(3); const int inputChannelBlocks = UP_DIV(inputChannels, 4); + const int blockDim = mResource->mInputChannel / mResource->mBlockSize; std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel) + "_" + std::to_string(mResource->mKernelHeight) + "_" + std::to_string(mResource->mKernelWidth) + "_" + std::to_string(mResource->mStrides[0]) + "_" + std::to_string(mResource->mStrides[1]) + "_" + std::to_string(mResource->mDilations[0]) + "_" + std::to_string(mResource->mDilations[1]); int inputImageShape[2] = {inputHeight, inputWidth}; int outputImageShape[2] = {height, width}; @@ -254,6 +273,9 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor if((outputShape.at(2) % itemW[knl_idx]) != 0 || (outputShape.at(1) % itemH[knl_idx]) != 0){ buildOption.emplace("-DBLOCK_LEAVE"); } + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_int_buf", kernelName[knl_idx], buildOption); uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); @@ -264,8 +286,7 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][1]); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(input)); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScale.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantOffset.get())); + ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(output)); ret |= kernel[knl_idx]->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); @@ -279,9 +300,10 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(width, itemW[knl_idx])); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(outChannel, 4)); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(height, itemH[knl_idx])); + ret |= kernel[knl_idx]->get().setArg(idx++, blockDim); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvBufLowMemory Kernel Select"); std::pair, int> retTune; - retTune = gws2dLwsTune(kernel[knl_idx], globalWorkSize[knl_idx], kernelName[knl_idx] + info, maxWorkGroupSize); + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); if(min_cost.first > retTune.second) { min_cost.first = retTune.second; min_cost.second = knl_idx; @@ -298,6 +320,9 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor if((outputShape.at(2) % itemW[min_index]) != 0 || (outputShape.at(1) % itemH[min_index]) != 0){ buildOption.emplace("-DBLOCK_LEAVE"); } + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d_int_buf", kernelName[min_index], buildOption); uint32_t idx = 0; @@ -306,8 +331,7 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScale.get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantOffset.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); ret |= unit.kernel->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); @@ -321,6 +345,7 @@ void ConvBufLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor ret |= unit.kernel->get().setArg(idx++, UP_DIV(width, itemW[min_index])); ret |= unit.kernel->get().setArg(idx++, UP_DIV(outChannel, 4)); ret |= unit.kernel->get().setArg(idx++, UP_DIV(height, itemH[min_index])); + ret |= unit.kernel->get().setArg(idx++, blockDim); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvBufLowMemory"); mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; @@ -338,6 +363,8 @@ void ConvBufLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * outpu const int width = outputShape.at(2); const int inputChannelBlocks = UP_DIV(inputChannels, 4); const int outputChannelBlocks = UP_DIV(outChannel, 4); + const int blockNum = mResource->mBlockSize; + const int blockDim = mResource->mInputChannel / mResource->mBlockSize; int global_y = batch * height; const int total_kernel = 5; @@ -353,9 +380,9 @@ void ConvBufLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * outpu buildOption.emplace("-DWIDTH_HEIGHT_1"); } - if(inputChannels % 16 != 0){ + if(blockDim % 16 != 0){ buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); - } else if (mResource->mUseImage && mNumQuantBit == 4 && inputChannels % 32 != 0) { + } else if (mResource->mUseImage && mResource->mNumQuantBit == 4 && blockDim % 32 != 0) { // Image weight-int4 use load32 buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); } @@ -386,18 +413,20 @@ void ConvBufLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * outpu }else{ ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelBuffer.get()); } - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScale.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantOffset.get())); + ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(output)); ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(outputChannelBlocks)); ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= kernel[knl_idx]->get().setArg(idx++, inputChannels); ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(batch)); ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(height)); ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(width)); + ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockNum)); + ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockDim)); MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf Kernel Select"); std::pair, int> retTune; - retTune = gws2dLwsTune(kernel[knl_idx], globalWorkSize[knl_idx], kernelName[knl_idx] + info, maxWorkGroupSize); + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); if(min_cost.first > retTune.second) { min_cost.first = retTune.second; min_cost.second = knl_idx; @@ -420,21 +449,177 @@ void ConvBufLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * outpu }else{ ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); } - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScale.get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantOffset.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelBlocks)); ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannels)); ret |= unit.kernel->get().setArg(idx++, static_cast(batch)); ret |= unit.kernel->get().setArg(idx++, static_cast(height)); ret |= unit.kernel->get().setArg(idx++, static_cast(width)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockNum)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf"); mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; return; } +void ConvBufLowMemoryExecution::tuneGemvBatchLowMemory(Tensor * input, Tensor * output) { + mUnits.resize(3); + std::vector inputShape = tensorShapeFormat(input); + std::vector outputShape = tensorShapeFormat(output); + const int outChannel = outputShape.at(3); + const int inputChannels = inputShape.at(3); + const int batch = outputShape.at(0); + const int width_height = outputShape.at(1) * outputShape.at(2); + const int inputChannelBlocks = UP_DIV(inputChannels, 4); + const int outputChannelBlocks = UP_DIV(outChannel, 4); + const int blockNum = mResource->mBlockSize; + const int blockDim = mResource->mInputChannel / mResource->mBlockSize; + + int global_y = UP_DIV(batch, 4) * width_height; + const int total_kernel = 5; + std::string kernelName[total_kernel] = {"gemm_b4_c1_buf", "gemm_b4_c2_buf", "gemm_b4_c4_buf", "gemm_b4_c1_image", "gemm_b4_c2_image"}; + int itemC[total_kernel] = {1, 2, 4, 1, 2}; + int actual_kernel = total_kernel; + std::shared_ptr kernel[total_kernel]; + std::vector globalWorkSize[total_kernel]; + std::vector localWorkSize[total_kernel]; + std::pair min_cost(INT_MAX, 0);//(min_time, min_index) + std::set buildOption = mResource->mBuildOptions; + if(blockDim % 16 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } else if (mResource->mUseImage && mResource->mNumQuantBit == 4 && blockDim % 32 != 0) { + // Image weight-int4 use load32 + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } + std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel); + // mResource->mInputChannel ROUND_UP to blockDim, avoid gemm overstep + mConvGemmInpTensor.reset(Tensor::createDevice({ROUND_UP(batch, 4) * ROUND_UP(ROUND_UP(mResource->mInputChannel, 4), blockDim) * width_height})); + mConvGemmOutTensor.reset(Tensor::createDevice({ROUND_UP(batch, 4) * ROUND_UP(mResource->mOutputChannel, 4) * width_height})); + mOpenCLBackend->onAcquireBuffer(mConvGemmInpTensor.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mConvGemmOutTensor.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mConvGemmOutTensor.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mConvGemmInpTensor.get(), Backend::DYNAMIC); + + // reshape n*c/4*4*hw -> n/4*hw*c*4 + { + auto &unit = mUnits[0]; + mGlobalWorkSize = {static_cast(UP_DIV(mResource->mInputChannel, 4)), static_cast(UP_DIV(batch, 4)), static_cast(width_height)}; + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_quant_batch_buf", "reshape_nchw4_nhwc4", buildOption); + uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); + + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[2]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmInpTensor.get())); + ret |= unit.kernel->get().setArg(idx++, static_cast(width_height)); + ret |= unit.kernel->get().setArg(idx++, static_cast(batch)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannels)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelBlocks)); + MNN_CHECK_CL_SUCCESS(ret, "setArg reshape_nc4_cn4"); + mLocalWorkSize = localWS3DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), "reshape_nchw4_nhwc4", unit.kernel).first; + mOpenCLBackend->recordKernel3d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); + unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1], mGlobalWorkSize[2]}; + unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1], mLocalWorkSize[2]}; + } + // gemm + { + auto &unit = mUnits[1]; + int knl_idx = 0; + actual_kernel = 3; + if(mResource->mUseImage){ + knl_idx = 3; + actual_kernel = total_kernel; + } + for (; knl_idx < actual_kernel; knl_idx++) { + kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_quant_batch_buf", kernelName[knl_idx], buildOption); + uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); + + globalWorkSize[knl_idx] = {static_cast(UP_DIV(outChannel, itemC[knl_idx])), static_cast(global_y)}; + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][0]); + ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][1]); + ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mConvGemmInpTensor.get())); + if(mResource->mUseImage){ + ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelImage.get()); + }else{ + ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelBuffer.get()); + } + ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); + ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mConvGemmOutTensor.get())); + ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(outputChannelBlocks)); + ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockNum)); + ret |= kernel[knl_idx]->get().setArg(idx++, static_cast(blockDim)); + MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf Kernel Select"); + std::pair, int> retTune; + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); + if(min_cost.first > retTune.second) { + min_cost.first = retTune.second; + min_cost.second = knl_idx; + mLocalWorkSize = {retTune.first[0], retTune.first[1]}; + } + } + int min_index = min_cost.second; + mGlobalWorkSize = {globalWorkSize[min_index][0], globalWorkSize[min_index][1]}; + + + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_quant_batch_buf", kernelName[min_index], buildOption); + //MNN_PRINT("Kernel is %d.\n", min_index); + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmInpTensor.get())); + if(mResource->mUseImage){ + ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelImage.get()); + }else{ + ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); + } + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->dequantScaleOffset.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mBias.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmOutTensor.get())); + ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelBlocks)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelBlocks)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockNum)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); + MNN_CHECK_CL_SUCCESS(ret, "setArg gemv_conv1x1_buf"); + mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); + unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1]}; + unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1]}; + } + // reshape n/4*hw*c*4 -> n*c/4*4*hw + { + auto &unit = mUnits[2]; + mGlobalWorkSize = {static_cast(UP_DIV(mResource->mOutputChannel, 4)), static_cast(UP_DIV(batch, 4)), static_cast(width_height)}; + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_quant_batch_buf", "reshape_nhwc4_nchw4", buildOption); + uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); + ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[2]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mConvGemmOutTensor.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); + ret |= unit.kernel->get().setArg(idx++, static_cast(width_height)); + ret |= unit.kernel->get().setArg(idx++, static_cast(batch)); + ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelBlocks)); + MNN_CHECK_CL_SUCCESS(ret, "setArg reshape_cn4_nc4"); + mLocalWorkSize = localWS3DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), "reshape_nhwc4_nchw4", unit.kernel).first; + mOpenCLBackend->recordKernel3d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); + unit.globalWorkSize = {mGlobalWorkSize[0], mGlobalWorkSize[1], mGlobalWorkSize[2]}; + unit.localWorkSize = {mLocalWorkSize[0], mLocalWorkSize[1], mLocalWorkSize[2]}; + } + return; +} ConvBufLowMemoryExecution::ConvBufLowMemoryExecution(const std::vector &inputs, const std::vector &outputs, const MNN::Op *op, Backend *backend) : ConvBufCommonExecution(op->main_as_Convolution2D(), backend), CommonExecution(backend, op) { #ifdef LOG_VERBOSE @@ -454,7 +639,6 @@ ConvBufLowMemoryExecution::ConvBufLowMemoryExecution(const std::vector mResource->mKernelWidth = conv2dCommonParams->kernelX(); mResource->mKernelHeight = conv2dCommonParams->kernelY(); mResource->mOutputChannel = conv2dCommonParams->outputCount(); - mResource->mInputChannel = conv2dCommonParams->inputCount(); std::shared_ptr quanCommon; // set mDequantScale, mDequantOffset, mFilterDataPtr // prepare mDequantScale mDequantOffset mFilterDataPtr @@ -473,15 +657,15 @@ ConvBufLowMemoryExecution::ConvBufLowMemoryExecution(const std::vector } else if (conv2dCommonParams->relu6()) { mResource->mBuildOptions.emplace("-DRELU6"); } - if (mNumQuantBit == 8) { + if (mResource->mNumQuantBit == 8) { // int8 case mResource->mBuildOptions.emplace("-DUSE_LOW_BIT_WEIGHT_INT8"); - } else if (mNumQuantBit == 4){ + } else if (mResource->mNumQuantBit == 4){ // int4 case mResource->mBuildOptions.emplace("-DUSE_LOW_BIT_WEIGHT_INT4"); } else {/* More types to be supported. */} #ifdef LOG_VERBOSE - MNN_PRINT("end ConvExecution init !\n"); + MNN_PRINT("end ConvBufLowMemoryExecution init !\n"); #endif } @@ -511,7 +695,7 @@ bool ConvBufLowMemoryExecution::onClone(Backend* bn, const Op* op, Execution** d ErrorCode ConvBufLowMemoryExecution::onEncode(const std::vector &inputs, const std::vector &outputs) { #ifdef LOG_VERBOSE - MNN_PRINT("Start ConvExecution onResize !\n"); + MNN_PRINT("Start ConvBufLowMemoryExecution onResize !\n"); #endif mUnits.resize(1); auto input = inputs[0]; @@ -520,13 +704,20 @@ ErrorCode ConvBufLowMemoryExecution::onEncode(const std::vector &input mPaddings[0] = padding.second;//padY mPaddings[1] = padding.first;//padX // onclone default use conv1x1Opt, need reset + std::vector outputShape = tensorShapeFormat(output); + const int batch = outputShape.at(0); + bool isMali = mOpenCLBackend->getOpenCLRuntime()->getGpuType() == MALI; if (mResource->mConv1x1Opt) { - tuneGemmLowMemory(input, output); + if(batch > 1 && isMali){ + tuneGemvBatchLowMemory(input, output); + }else{ + tuneGemmLowMemory(input, output); + } } else { tuneGeneralCaseLowMemory(input, output); } #ifdef LOG_VERBOSE - MNN_PRINT("end ConvExecution onResize !\n"); + MNN_PRINT("end ConvBufLowMemoryExecution onResize !\n"); #endif return NO_ERROR; } diff --git a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp index 8a99c7afc..de0938c7b 100644 --- a/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp +++ b/source/backend/opencl/execution/buffer/ConvBufLowMemoryExecution.hpp @@ -29,12 +29,16 @@ class ConvBufLowMemoryExecution : public ConvBufCommonExecution, public CommonEx void setGeneralWeightLowMemory(void * filterDataPtr, std::shared_ptr & quanCommon); void tuneGeneralCaseLowMemory(Tensor * input, Tensor * output); void tuneGemmLowMemory(Tensor * input, Tensor * output); + void tuneGemvBatchLowMemory(Tensor * input, Tensor * output); + bool convertToQuantWeight1x1Buffer(cl::Buffer input, int pack); std::vector mPaddings{0, 0}; std::vector mGlobalWorkSize{1, 1, 1}; std::vector mLocalWorkSize{1, 1, 1, 1}; void *mFilterDataPtr = nullptr; bool mLowMemoryFlag = false; - int mNumQuantBit = 0; + std::shared_ptr mConvGemmInpTensor; + std::shared_ptr mConvGemmOutTensor; + std::shared_ptr mBufferToConv1x1Kernel = nullptr; }; } // namespace OpenCL diff --git a/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp b/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp index 5ddba38fb..52c0d39c2 100644 --- a/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp +++ b/source/backend/opencl/execution/buffer/ConvBufWinograd.cpp @@ -30,7 +30,44 @@ bool ConvBufWinograd::valid(const Convolution2DCommon* common, const Tensor* inp return input->width() * input->height() <= 4096; } - return input->channel() >= 32 && output->channel() >= 32 && input->width() < output->channel(); + bool valid = input->channel() >= 32 && output->channel() >= 32 && input->width() < output->channel(); + valid = valid || (input->channel() >= 64 && output->channel() >= 64); + return valid; +} + +void ConvBufWinograd::convertWeightFormat(cl::Buffer& buffer, const int tileK, const int tileN) { + auto runtime = mOpenCLBackend->getOpenCLRuntime(); + + auto icPad = ROUND_UP(mCi, tileK); + auto ocPad = ROUND_UP(mCo, tileN); + + auto kernel = runtime->buildKernel("winogradTransform_buf", "winoTransWeightBuf2_3_1", {}); + uint32_t gws[2] = {static_cast(icPad), static_cast(ocPad)}; + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= kernel->get().setArg(idx++, gws[0]); + ret |= kernel->get().setArg(idx++, gws[1]); + ret |= kernel->get().setArg(idx++, buffer); + ret |= kernel->get().setArg(idx++, openCLBuffer(mResource->mWeight.get())); + ret |= kernel->get().setArg(idx++, mCi); + ret |= kernel->get().setArg(idx++, mCo); + ret |= kernel->get().setArg(idx++, icPad); + ret |= kernel->get().setArg(idx++, ocPad); + + MNN_CHECK_CL_SUCCESS(ret, "setArg conv-winograd convertWeightFormat"); + const std::vector lws = {8, 8}; + cl::Event event; + cl_int res; + std::vector roundUpGroupWorkSize(lws.size()); + for (size_t i = 0; i < lws.size(); ++i) { + roundUpGroupWorkSize[i] = ROUND_UP(gws[i], lws[i]); + } + res = runtime->commandQueue().enqueueNDRangeKernel(kernel->get(), cl::NullRange, + cl::NDRange(roundUpGroupWorkSize[0], roundUpGroupWorkSize[1]), + cl::NDRange(lws[0], lws[1]), nullptr, &event); + MNN_CHECK_CL_SUCCESS(res, "conv-winograd convertWeightFormat"); + //event.wait(); + return; } ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonExecution(backend, op) { @@ -50,10 +87,10 @@ ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonEx std::shared_ptr quanCommon; ConvolutionCommon::getConvParameters(&quanCommon, backend, conv2D, &filterDataPtr, &weightSize); - int oc = mResource->mCommon->outputCount(); - int ic = weightSize / oc / mResource->mCommon->kernelX() / mResource->mCommon->kernelY(); - auto ocC4 = UP_DIV(oc, 4); - auto icC4 = UP_DIV(ic, 4); + mCo = mResource->mCommon->outputCount(); + mCi = weightSize / mCo / mResource->mCommon->kernelX() / mResource->mCommon->kernelY(); + auto ocC4 = UP_DIV(mCo, 4); + auto icC4 = UP_DIV(mCi, 4); auto queue = runTime->commandQueue(); auto imageChannelType = CL_HALF_FLOAT; @@ -66,7 +103,7 @@ ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonEx if (mResource->mUseSubgroup) { // create buffer for intel subgroup cl_int ret_code; - size_t bias_element = ALIGN_UP4(oc); + size_t bias_element = ALIGN_UP4(mCo); size_t buffer_size; if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()) { buffer_size = bias_element * sizeof(half_float::half); @@ -74,7 +111,7 @@ ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonEx buffer_size = bias_element * sizeof(float); } - mResource->mBias.reset(Tensor::createDevice({1, 1, 1, (int)ALIGN_UP4(oc)})); + mResource->mBias.reset(Tensor::createDevice({1, 1, 1, (int)ALIGN_UP4(mCo)})); mOpenCLBackend->onAcquireBuffer(mResource->mBias.get(), Backend::STATIC); cl::Buffer &bias_buffer = *(cl::Buffer *)mResource->mBias->buffer().device; @@ -84,19 +121,19 @@ ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonEx } ::memset(bias_ptr, 0, buffer_size); if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()) { - for(int i=0; ibias()->data()[i]; } } else { - ::memcpy(bias_ptr, conv2D->bias()->data(), oc*sizeof(float)); + ::memcpy(bias_ptr, conv2D->bias()->data(), mCo*sizeof(float)); } queue.enqueueUnmapMemObject(bias_buffer, bias_ptr); - auto ocC16 = UP_DIV(oc, 16); - auto icC16 = UP_DIV(ic, 16); + auto ocC16 = UP_DIV(mCo, 16); + auto icC16 = UP_DIV(mCi, 16); std::shared_ptr sourceWeight( - Tensor::create(std::vector{oc, ic, ky, kx}, (void*)(filterDataPtr), Tensor::CAFFE)); + Tensor::create(std::vector{mCo, mCi, ky, kx}, (void*)(filterDataPtr), Tensor::CAFFE)); int unit = UNIT; int kernelSize = kx; @@ -136,8 +173,9 @@ ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonEx }else #endif /* MNN_SUPPORT_INTEL_SUBGROUP */ { + cl_int ret_code; - size_t bias_element = ALIGN_UP4(oc); + size_t bias_element = ALIGN_UP4(mCo); size_t buffer_size; if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()) { buffer_size = bias_element * sizeof(half_float::half); @@ -145,63 +183,52 @@ ConvBufWinograd::ConvBufWinograd(const MNN::Op* op, Backend* backend) : CommonEx buffer_size = bias_element * sizeof(float); } - mResource->mBias.reset(Tensor::createDevice({1, 1, 1, (int)ALIGN_UP4(oc)})); + mResource->mBias.reset(Tensor::createDevice({1, 1, 1, (int)ALIGN_UP4(mCo)})); mOpenCLBackend->onAcquireBuffer(mResource->mBias.get(), Backend::STATIC); cl::Buffer &bias_buffer = *(cl::Buffer *)mResource->mBias->buffer().device; - + auto bias_ptr = queue.enqueueMapBuffer(bias_buffer, CL_TRUE, CL_MAP_WRITE, 0, buffer_size, nullptr, nullptr, &ret_code); if(bias_ptr == nullptr || ret_code) { MNN_ERROR("clBuffer map error!\n"); } ::memset(bias_ptr, 0, buffer_size); if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()) { - for(int i=0; ibias()->data()[i]; } } else { - ::memcpy(bias_ptr, conv2D->bias()->data(), oc*sizeof(float)); + ::memcpy(bias_ptr, conv2D->bias()->data(), mCo*sizeof(float)); } queue.enqueueUnmapMemObject(bias_buffer, bias_ptr); - - std::shared_ptr sourceWeight( - Tensor::create(std::vector{oc, ic, ky, kx}, (void*)(filterDataPtr), Tensor::CAFFE)); - int unit = UNIT; int kernelSize = kx; - Math::WinogradGenerater generator(unit, kernelSize, INTERP); int alpha = unit + kernelSize - 1; - auto weightDest = generator.allocTransformWeight(sourceWeight.get()); - generator.transformWeight(weightDest.get(), sourceWeight.get()); - auto weightDestSize = weightDest->size(); - - buffer_size = weightDest->elementSize(); - if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()) { - buffer_size *= sizeof(half_float::half); - } else { - buffer_size *= sizeof(float); - } - mResource->mWeight.reset(Tensor::createDevice({1, ocC4 * alpha * alpha, icC4 * 4, 4}));//NHWC + int tileK = 16; + int tileN = 32; + + std::shared_ptr tmpFilterTensor; + tmpFilterTensor.reset(Tensor::createDevice({mCo * mCi * ky * kx})); + mOpenCLBackend->onAcquireBuffer(tmpFilterTensor.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(tmpFilterTensor.get(), Backend::DYNAMIC); + + mResource->mWeight.reset(Tensor::createDevice({alpha * alpha * ROUND_UP(mCo, tileN) * ROUND_UP(mCi, tileK)}));//NHWC mOpenCLBackend->onAcquireBuffer(mResource->mWeight.get(), Backend::STATIC); - cl::Buffer &weightBuffer = *(cl::Buffer *)mResource->mWeight->buffer().device; - - auto weight_ptr = queue.enqueueMapBuffer(weightBuffer, CL_TRUE, CL_MAP_WRITE, 0, buffer_size, nullptr, nullptr, &ret_code); - if(weight_ptr != nullptr && ret_code == CL_SUCCESS){ - if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ - for(int i=0; ielementSize(); i++) { - ((half_float::half*)weight_ptr)[i] = (half_float::half)(weightDest->host()[i]); - } - }else{ - ::memcpy(weight_ptr, weightDest->host(), buffer_size); - } - } else{ - MNN_ERROR("Map error weightPtr == nullptr \n"); + buffer_size = mCo * mCi * ky * kx * sizeof(float); + cl::Buffer& weightBufferCL = openCLBuffer(tmpFilterTensor.get()); + + cl_int res; + auto ptrCL = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(weightBufferCL, true, CL_MAP_WRITE, 0, buffer_size, nullptr, nullptr, &res); + if(ptrCL != nullptr && res == CL_SUCCESS) { + ::memcpy(ptrCL, filterDataPtr, buffer_size); + }else{ + MNN_ERROR("Map weightBufferCL error:%d, ptrCL == nullptr \n", res); } - - queue.enqueueUnmapMemObject(weightBuffer, weight_ptr); + mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(weightBufferCL, ptrCL); + convertWeightFormat(weightBufferCL, tileK, tileN); } } @@ -431,11 +458,13 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st } else #endif /* MNN_SUPPORT_INTEL_SUBGROUP */ { + int tileM = 16; + int tileN = 32; + int tileK = 16; mSource.reset(Tensor::createDevice( - std::vector{alpha * alpha, input->channel(), ROUND_UP(UP_DIV(wUnit * hUnit, 4), 2), 4}, - Tensor::CAFFE_C4)); + std::vector{alpha * alpha * ROUND_UP(input->channel(), tileK) * ROUND_UP(wUnit * hUnit, tileM)})); mDest.reset(Tensor::createDevice( - std::vector{4, wUnit * hUnit, UP_DIV(output->channel(), 4), alpha * alpha}, Tensor::CAFFE_C4)); + std::vector{alpha * alpha * ROUND_UP(wUnit * hUnit, tileM) * ROUND_UP(output->channel(), tileN)})); mOpenCLBackend->onAcquireBuffer(mSource.get(), Backend::DYNAMIC); mOpenCLBackend->onAcquireBuffer(mDest.get(), Backend::DYNAMIC); @@ -467,13 +496,16 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st } } + int hCount = hUnit; + int wCount = wUnit; + int M_pack = ROUND_UP(wCount * hCount, tileM); + int K_pack = ROUND_UP(input->channel(), tileK); + int N_pack = ROUND_UP(output->channel(), tileN); for (int b = 0; b < input->batch(); ++b) { - int hCount = hUnit; - int wCount = wUnit; // Source Transform { - mGWS_S[b] = {static_cast(wCount * hCount), static_cast(icC4)}; + mGWS_S[b] = {static_cast(M_pack), static_cast(UP_DIV(K_pack, 4))}; int index = 0; cl_int ret = CL_SUCCESS; ret |= mUnits[b * 3].kernel->get().setArg(index++, mGWS_S[b][0]); @@ -487,8 +519,10 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st ret |= mUnits[b * 3].kernel->get().setArg(index++, input->width()); ret |= mUnits[b * 3].kernel->get().setArg(index++, input->height()); ret |= mUnits[b * 3].kernel->get().setArg(index++, icC4); + ret |= mUnits[b * 3].kernel->get().setArg(index++, M_pack); + ret |= mUnits[b * 3].kernel->get().setArg(index++, K_pack); ret |= mUnits[b * 3].kernel->get().setArg(index++, b); - MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf SubGroup Source Trans"); + MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf Source Trans"); std::string kernelName = "winoTransSrcBuf"; mLWS_S[b] = localWS2DDefault(mGWS_S[b], mMaxWGS_S[b], mOpenCLBackend->getOpenCLRuntime(), kernelName + info, mUnits[b * 3].kernel).first; @@ -498,70 +532,86 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st } // MatMul + { - auto gemmHeight = ocC4; - auto gemmWidth = UP_DIV(wCount * hCount, 4); - - const int total_kernel = 2; - const std::string kernelName[total_kernel] = {"gemm_buf", "gemm_buf2"}; - int itemW[total_kernel] = {1, 2}; - - int actual_kernel = total_kernel; - if (mOpenCLBackend->getOpenCLRuntime()->getCLTuneLevel() == Normal || mOpenCLBackend->getOpenCLRuntime()->getCLTuneLevel() == Fast || mOpenCLBackend->getOpenCLRuntime()->getCLTuneLevel() == None) { - actual_kernel = 1; + int loop = alpha * alpha; + int e_pack = ROUND_UP(wCount * hCount, tileM); + int l_pack = ROUND_UP(input->channel(), tileK); + int h_pack = ROUND_UP(output->channel(), tileN); + + std::set buildOptions; + uint32_t layout = 4; + auto param = getGemmParams({(uint32_t)e_pack, (uint32_t)h_pack, (uint32_t)l_pack, layout, (uint32_t)loop}, {openCLBuffer(mSource.get()), openCLBuffer(mResource->mWeight.get()), openCLBuffer(mDest.get())}, mOpenCLBackend->getOpenCLRuntime()); + + int GEMMK=param[0], KREG=param[1], KWG=param[2], KWI=param[3], MDIMA=param[4], MDIMC=param[5], MWG=param[6], NDIMB=param[7], NDIMC=param[8], NWG=param[9], SA=param[10], SB=param[11], STRM=param[12], STRN=param[13], VWM=param[14], VWN=param[15]; + buildOptions.emplace("-DGEMMK=" + std::to_string(GEMMK)); + buildOptions.emplace("-DKREG=" + std::to_string(KREG)); + buildOptions.emplace("-DKWG=" + std::to_string(KWG)); + buildOptions.emplace("-DKWI=" + std::to_string(KWI)); + buildOptions.emplace("-DMDIMA=" + std::to_string(MDIMA)); + buildOptions.emplace("-DMDIMC=" + std::to_string(MDIMC)); + buildOptions.emplace("-DMWG=" + std::to_string(MWG)); + buildOptions.emplace("-DNDIMB=" + std::to_string(NDIMB)); + buildOptions.emplace("-DNDIMC=" + std::to_string(NDIMC)); + buildOptions.emplace("-DNWG=" + std::to_string(NWG)); + buildOptions.emplace("-DSA=" + std::to_string(SA)); + buildOptions.emplace("-DSB=" + std::to_string(SB)); + buildOptions.emplace("-DSTRM=" + std::to_string(STRM)); + buildOptions.emplace("-DSTRN=" + std::to_string(STRN)); + buildOptions.emplace("-DVWM=" + std::to_string(VWM)); + buildOptions.emplace("-DVWN=" + std::to_string(VWN)); + if(layout >= 4) { + buildOptions.emplace("-DOUTPUTMN"); } - - std::shared_ptr kernel[total_kernel]; - std::vector globalWorkSize[total_kernel]; - std::vector localWorkSize[total_kernel]; - std::pair min_cost(UINT_MAX, 0); //(min_time, min_index) - for (int knl_idx = 0; knl_idx < actual_kernel; knl_idx++) { - kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_buf", kernelName[knl_idx], basic); - uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); - - globalWorkSize[knl_idx] = {static_cast(UP_DIV(gemmWidth, itemW[knl_idx]) * gemmHeight), static_cast(alpha * alpha)}; - uint32_t index = 0; - cl_int ret = CL_SUCCESS; - ret |= kernel[knl_idx]->get().setArg(index++, globalWorkSize[knl_idx][0]); - ret |= kernel[knl_idx]->get().setArg(index++, globalWorkSize[knl_idx][1]); - ret |= kernel[knl_idx]->get().setArg(index++, openCLBuffer(mSource.get())); - ret |= kernel[knl_idx]->get().setArg(index++, openCLBuffer(mResource->mWeight.get())); - ret |= kernel[knl_idx]->get().setArg(index++, openCLBuffer(mDest.get())); - ret |= kernel[knl_idx]->get().setArg(index++, gemmWidth); - ret |= kernel[knl_idx]->get().setArg(index++, gemmHeight); - ret |= kernel[knl_idx]->get().setArg(index++, icC4); - ret |= kernel[knl_idx]->get().setArg(index++, alpha * alpha); - MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf SubGroup MatMul Kernel Select"); - - std::pair, uint32_t> retTune; - retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); - // printf("gemm %d, %d\n", knl_idx, retTune.second); - if (min_cost.first > retTune.second) { - min_cost.first = retTune.second; - min_cost.second = knl_idx; - mLWS_M[b] = {retTune.first[0], retTune.first[1]}; - } + + int tileM = MWG; + int tileN = NWG; + int localM = MDIMC; + int localN = NDIMC; + + if(mOpenCLBackend->getOpenCLRuntime()->getGpuType() == GpuType::ADRENO) { + buildOptions.emplace("-DUSE_CL_MAD=1"); + buildOptions.emplace("-DRELAX_WORKGROUP_SIZE=1"); } - int min_index = min_cost.second; - // mKernel = kernel[min_index]; - mGWS_M[b] = {globalWorkSize[min_index][0], globalWorkSize[min_index][1]}; - mUnits[b * 3 + 1].kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm_buf", kernelName[min_index], basic); - int index = 0; + if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ + buildOptions.emplace(" -DPRECISION=16"); + } else { + buildOptions.emplace(" -DPRECISION=32"); + } + + mUnits[b * 3 + 1].kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); + + int out_per_thread_m = tileM / localM; + int out_per_thread_n = tileN / localN; + + mGWS_M[b] = {static_cast(e_pack/out_per_thread_m), static_cast(h_pack/out_per_thread_n), static_cast(loop)}; + mLWS_M[b] = {static_cast(localM), static_cast(localN), 1}; + + float alpha = 1.0f; + float beta = 0.0f; + + int idx = 0; cl_int ret = CL_SUCCESS; - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, mGWS_M[b][0]); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, mGWS_M[b][1]); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, openCLBuffer(mSource.get())); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, openCLBuffer(mResource->mWeight.get())); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, openCLBuffer(mDest.get())); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, gemmWidth); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, gemmHeight); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, icC4); - ret |= mUnits[b * 3 + 1].kernel->get().setArg(index++, alpha * alpha); - MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf SubGroup MatMul"); - mOpenCLBackend->recordKernel2d(mUnits[b * 3 + 1].kernel, mGWS_M[b], mLWS_M[b]); - mUnits[b * 3 + 1].globalWorkSize = {mGWS_M[b][0], mGWS_M[b][1]}; - mUnits[b * 3 + 1].localWorkSize = {mLWS_M[b][0], mLWS_M[b][1]}; + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, static_cast(e_pack)); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, static_cast(h_pack)); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, static_cast(l_pack)); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, alpha); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, beta); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, openCLBuffer(mSource.get())); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, e_pack); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, l_pack); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, openCLBuffer(mResource->mWeight.get())); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, h_pack); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, l_pack); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, openCLBuffer(mDest.get())); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, e_pack); + ret |= mUnits[b * 3 + 1].kernel->get().setArg(idx++, h_pack); + MNN_CHECK_CL_SUCCESS(ret, "setArg Winograd batchmatmul Kernel"); + + mOpenCLBackend->recordKernel3d(mUnits[b * 3 + 1].kernel, mGWS_M[b], mLWS_M[b]); + mUnits[b * 3 + 1].globalWorkSize = {mGWS_M[b][0], mGWS_M[b][1], mGWS_M[b][2]}; + mUnits[b * 3 + 1].localWorkSize = {mLWS_M[b][0], mLWS_M[b][1], mLWS_M[b][2]}; } // Dest Transform @@ -580,8 +630,10 @@ ErrorCode ConvBufWinograd::onEncode(const std::vector& inputs, const st ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, output->width()); ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, output->height()); ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, ocC4); + ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, M_pack); + ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, N_pack); ret |= mUnits[b * 3 + 2].kernel->get().setArg(index++, b); - MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf SubGroup Dest Trans"); + MNN_CHECK_CL_SUCCESS(ret, "setArg ConvWinogradBuf Dest Trans"); std::string kernelName = "winoTransDstBuf"; mLWS_D[b] = localWS2DDefault(mGWS_D[b], mMaxWGS_D[b], mOpenCLBackend->getOpenCLRuntime(), kernelName + info, mUnits[b * 3 + 2].kernel).first; @@ -647,7 +699,7 @@ ErrorCode ConvBufWinograd::onExecute(const std::vector &inputs, const unit.globalWorkSize, unit.localWorkSize); #endif - MNN_CHECK_CL_SUCCESS(res, "While-gemm execute"); + MNN_CHECK_CL_SUCCESS(res, "Conv-Winograd execute"); } return NO_ERROR; } diff --git a/source/backend/opencl/execution/buffer/ConvBufWinograd.hpp b/source/backend/opencl/execution/buffer/ConvBufWinograd.hpp index 4cfe2abc7..e200fc2ef 100644 --- a/source/backend/opencl/execution/buffer/ConvBufWinograd.hpp +++ b/source/backend/opencl/execution/buffer/ConvBufWinograd.hpp @@ -39,6 +39,9 @@ class ConvBufWinograd : public CommonExecution { #ifdef MNN_SUPPORT_INTEL_SUBGROUP ErrorCode SubgroupOnResize(const std::vector &inputs, const std::vector &outputs); #endif /* MNN_SUPPORT_INTEL_SUBGROUP */ + +private: + void convertWeightFormat(cl::Buffer& buffer, const int tileK, const int tileN); private: OpenCLBackend* mOpenCLBackend; std::shared_ptr mResource; @@ -46,6 +49,8 @@ class ConvBufWinograd : public CommonExecution { int mKernelY; int mStrideX; int mStrideY; + int mCi; + int mCo; std::shared_ptr mSource; std::shared_ptr mDest; diff --git a/source/backend/opencl/execution/buffer/DepthwiseConvBufExecution.cpp b/source/backend/opencl/execution/buffer/DepthwiseConvBufExecution.cpp index 606e0bda4..4e541fc4c 100644 --- a/source/backend/opencl/execution/buffer/DepthwiseConvBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/DepthwiseConvBufExecution.cpp @@ -124,6 +124,7 @@ ErrorCode DepthwiseConvBufExecution::onEncode(const std::vector &input int kernelShape[2] = {filterHeight, filterWidth}; int dilationShape[2] = {mResource->mDilations[0], mResource->mDilations[1]}; + std::string info = std::to_string(inputChannels) + "_" + std::to_string(outputChannel) + "_" + std::to_string(filterHeight) + "_" + std::to_string(filterWidth) + "_" + std::to_string(mResource->mStrides[0]) + "_" + std::to_string(mResource->mStrides[1]) + "_" + std::to_string(mResource->mDilations[0]) + "_" + std::to_string(mResource->mDilations[1]); if(mStride_1) { // {"depthwise_conv2d_s1_c4h1w4", "depthwise_conv2d_s1_c8h1w4", "depthwise_conv2d_s1_c8h1w2"}; const int total_kernel = 3; @@ -183,7 +184,7 @@ ErrorCode DepthwiseConvBufExecution::onEncode(const std::vector &input MNN_CHECK_CL_SUCCESS(ret, "setArg DepthwiseConvBufExecution Stride_1 Kernel Select"); std::pair, int> retTune; - retTune = gws2dLwsTune(kernel[knl_idx], globalWorkSize[knl_idx], kernelName[knl_idx], maxWorkGroupSize); + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); //printf("depthwiseCovs1 %d, %d\n", knl_idx, retTune.second); if(min_cost.first > retTune.second) { min_cost.first = retTune.second; @@ -259,7 +260,7 @@ ErrorCode DepthwiseConvBufExecution::onEncode(const std::vector &input MNN_CHECK_CL_SUCCESS(ret, "setArg DepthwiseConvBufExecution Kernel Select"); std::pair, int> retTune; - retTune = gws2dLwsTune(kernel[knl_idx], globalWorkSize[knl_idx], kernelName[knl_idx], maxWorkGroupSize); + retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); //printf("depthwiseCov!! %d, %d\n", knl_idx, retTune.second); if(min_cost.first > retTune.second) { min_cost.first = retTune.second; diff --git a/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp b/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp new file mode 100644 index 000000000..e2aaf0194 --- /dev/null +++ b/source/backend/opencl/execution/buffer/GroupNormBufExecution.cpp @@ -0,0 +1,267 @@ + +// +// GroupNormBufExecution.cpp +// MNN +// +// Created by MNN on 2024/06/24. +// Copyright © 2018, Alibaba Group Holding Limited +// +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE + +#include "backend/opencl/execution/buffer/GroupNormBufExecution.hpp" + +namespace MNN { +namespace OpenCL { + +GroupNormBufExecution::GroupNormBufExecution(const MNN::Op* op, Backend* backend) : CommonExecution(backend, op) { + auto group_norm_param = op->main_as_GroupNorm(); + mOpenCLBackend = static_cast(backend); + auto runtime = mOpenCLBackend->getOpenCLRuntime(); + mEpsilon = group_norm_param->epsilon(); + mBSwish = group_norm_param->bSwish(); + mGroup = group_norm_param->group(); + if (group_norm_param->gamma() && group_norm_param->beta()) { + auto bufferUnitSize = runtime->isSupportedFP16() ? sizeof(half_float::half) : sizeof(float); + + mHasGammaBeta = true; + int size = group_norm_param->gamma()->size(); + mGammaTensor.reset(Tensor::createDevice({ALIGN_UP4(size)})); + auto status = backend->onAcquireBuffer(mGammaTensor.get(), Backend::STATIC); + if (!status) { + MNN_ERROR("Out of memory when gamma is acquired in GroupNorm.\n"); + } + + cl::Buffer &gammaBuffer = openCLBuffer(mGammaTensor.get()); + + cl_int res; + auto GammaPtrCL = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer( + gammaBuffer, true, CL_MAP_WRITE, 0, ALIGN_UP4(size) * bufferUnitSize, nullptr, nullptr, &res); + if(GammaPtrCL != nullptr && res == CL_SUCCESS){ + if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ + for (int i = 0; i < size; i++) { + ((half_float::half*)GammaPtrCL)[i] = (half_float::half)(group_norm_param->gamma()->data()[i]); + } + for(int i=size; igamma()->data(), size * sizeof(float)); + } + } else { + MNN_ERROR("GroupNorm Gamma map error:%d\n", res); + } + + + if (group_norm_param->beta()->size() != size) { + MNN_ERROR("Size of gamma and beta are not match in GroupNorm.\n"); + } + mBetaTensor.reset(Tensor::createDevice({ALIGN_UP4(size)})); + status = backend->onAcquireBuffer(mBetaTensor.get(), Backend::STATIC); + if (!status) { + MNN_ERROR("Out of memory when beta is acquired in GroupNorm.\n"); + } + + cl::Buffer &betaBuffer = openCLBuffer(mBetaTensor.get()); + + auto BetaPtrCL = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer( + betaBuffer, true, CL_MAP_WRITE, 0, ALIGN_UP4(size) * bufferUnitSize, nullptr, nullptr, &res); + if(BetaPtrCL != nullptr && res == CL_SUCCESS){ + if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ + for (int i = 0; i < size; i++) { + ((half_float::half*)BetaPtrCL)[i] = (half_float::half)(group_norm_param->beta()->data()[i]); + } + for(int i=size; ibeta()->data(), size * sizeof(float)); + } + } else { + MNN_ERROR("GroupNorm Beta map error:%d\n", res); + } + } +} + +int GroupNormBufExecution::getLocalSize(int size, int maxGroupSize){ + int local_size = 1; + while(local_size * 2 <= maxGroupSize && local_size * 2 <= size){ + local_size *= 2; + } + return local_size; +} +ErrorCode GroupNormBufExecution::onEncode(const std::vector& inputs, const std::vector& outputs) { + auto runtime = static_cast(backend())->getOpenCLRuntime(); + + MNN_ASSERT(outputs.size() == 1); + auto input = inputs[0]; + auto output = outputs[0]; + MNN_ASSERT(input->dimensions() == 4); + MNN_ASSERT(output->dimensions() == 4); + mBatch = input->length(0); + if(inputs.size() > 1) { + MNN_ASSERT(inputs[1]->dimensions() == 2); + MNN_ASSERT(inputs[1]->length(0) == inputs[0]->length(0)); + MNN_ASSERT(inputs[1]->length(1) == inputs[0]->length(1)); + } + + size_t outter_size = mBatch * mGroup; + size_t inner_size = 1; + for (int i = 1; i < input->dimensions(); i++) { + inner_size *= inputs[0]->length(i); + } + inner_size /= mGroup; + + mUnits.clear(); + mUnits.resize(3); + std::vector inputShape = tensorShapeFormat(inputs[0]); + int inputWH[] = {inputShape[2], inputShape[1]}; + int region[] = {inputShape[0], UP_DIV(inputShape[3], 4), inputShape[1], inputShape[2]}; + + mInputPlain = std::make_shared(Tensor::createDevice(std::vector{inputShape[0] * inputShape[3] * ROUND_UP(inputShape[1] * inputShape[2], 4)})); + mOpenCLBackend->onAcquireBuffer(mInputPlain.get(), Backend::DYNAMIC); + mOutputPlain = std::make_shared(Tensor::createDevice(std::vector{inputShape[0] * inputShape[3] * ROUND_UP(inputShape[1] * inputShape[2], 4)})); + mOpenCLBackend->onAcquireBuffer(mOutputPlain.get(), Backend::DYNAMIC); + + mOpenCLBackend->onReleaseBuffer(mInputPlain.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mOutputPlain.get(), Backend::DYNAMIC); + std::set buildOptions; + // convert nc4hw4 to nchw + { + auto &unit = mUnits[0]; + unit.kernel = runtime->buildKernel("buffer_convert_buf", "nc4hw4_buffer_to_nchw_buffer", {}, inputs[0], outputs[0]); + + mGWS = {(uint32_t)(UP_DIV(region[3] * region[1], 16) * 16), + (uint32_t)(UP_DIV(region[2] * region[0], 16) * 16)}; + mLWS = {16, 16}; + unit.globalWorkSize = {mGWS[0], mGWS[1]}; + unit.localWorkSize = {mLWS[0], mLWS[1]}; + + int global_dim0 = region[3] * region[1]; + int global_dim1 = region[2] * region[0]; + + //MNN_CHECK_CL_SUCCESS + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, global_dim0); + ret |= unit.kernel->get().setArg(idx++, global_dim1); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mInputPlain.get())); + ret |= unit.kernel->get().setArg(idx++, inputWH[1]); + ret |= unit.kernel->get().setArg(idx++, inputWH[0]); + ret |= unit.kernel->get().setArg(idx++, inputShape[3]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); + MNN_CHECK_CL_SUCCESS(ret, "setArg GroupNormBufExecution with group, convert nc4hw4 to nchw"); + + mOpenCLBackend->recordKernel2d(unit.kernel, mGWS, mLWS); + } + // do groupnorm + { + int area = inputWH[1] * inputWH[0]; + if(mHasGammaBeta){ + buildOptions.emplace("-DGAMMA_BETA"); + } + if(mBSwish) { + buildOptions.emplace("-DSWISH"); + } + if(area % 4 == 0) { + buildOptions.emplace("-DWH_4"); + } + if(inputs.size() > 1) { + buildOptions.emplace("-DDOUBLE_INPUTS"); + } + auto MaxLocalSize = std::min(runtime->getMaxWorkItemSizes()[0], (uint32_t)256); + + auto &unit = mUnits[1]; + std::string kernelName = "groupnorm_plain_buf"; + int local_size = getLocalSize(UP_DIV(inner_size, 4), MaxLocalSize); + buildOptions.emplace("-DLOCAL_SIZE=" + std::to_string(local_size)); + unit.kernel = runtime->buildKernel("groupnorm_buf", kernelName, buildOptions); + + mGWS = {static_cast(local_size), + static_cast(1), + static_cast(outter_size)}; + + mLWS = {static_cast(local_size), 1, 1}; + + unit.globalWorkSize = {mGWS[0], mGWS[1], mGWS[2]}; + unit.localWorkSize = {mLWS[0], mLWS[1], mLWS[2]}; + + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, mGWS[0]); + ret |= unit.kernel->get().setArg(idx++, mGWS[1]); + ret |= unit.kernel->get().setArg(idx++, mGWS[2]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mInputPlain.get())); + if(inputs.size() > 1) { + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(inputs[1])); + } + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mOutputPlain.get())); + ret |= unit.kernel->get().setArg(idx++, static_cast(area)); + ret |= unit.kernel->get().setArg(idx++, static_cast(mGroup)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inner_size)); + ret |= unit.kernel->get().setArg(idx++, static_cast(outter_size)); + if(mHasGammaBeta){ + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mGammaTensor.get())); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mBetaTensor.get())); + } + ret |= unit.kernel->get().setArg(idx++, mEpsilon); + MNN_CHECK_CL_SUCCESS(ret, "setArg GroupNormBufExecution with group, do group layernorm"); + mOpenCLBackend->recordKernel3d(unit.kernel, mGWS, mLWS); + } + // convert nchw to nc4hw4 + { + auto &unit = mUnits[2]; + + unit.kernel = runtime->buildKernel("buffer_convert_buf", "nchw_buffer_to_nc4hw4_buffer", {}, inputs[0], outputs[0]); + mLWS = {16, 16}; + mGWS = {(uint32_t)UP_DIV(region[3] * region[1], 16) * 16, + (uint32_t)UP_DIV(region[2] * region[0], 16) * 16}; + + unit.globalWorkSize = {mGWS[0], mGWS[1]}; + unit.localWorkSize = {mLWS[0], mLWS[1]}; + + int global_dim0 = region[3] * region[1]; + int global_dim1 = region[2] * region[0]; + + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, global_dim0); + ret |= unit.kernel->get().setArg(idx++, global_dim1); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mOutputPlain.get())); + ret |= unit.kernel->get().setArg(idx++, inputWH[1]); + ret |= unit.kernel->get().setArg(idx++, inputWH[0]); + ret |= unit.kernel->get().setArg(idx++, inputShape[3]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); + MNN_CHECK_CL_SUCCESS(ret, "setArg GroupNormBufExecution with group, convert nchw to nc4hw4"); + mOpenCLBackend->recordKernel2d(unit.kernel, mGWS, mLWS); + } + mOpenCLBackend->endRecord(mRecording); + + return NO_ERROR; + +} + + +class GroupNormBufCreator : public OpenCLBackend::Creator { +public: + virtual ~GroupNormBufCreator() = default; + virtual Execution *onCreate(const std::vector &inputs, const std::vector &outputs, + const MNN::Op *op, Backend *backend) const override { + for (int i = 0; i < inputs.size(); ++i) { + TensorUtils::setTensorSupportPack(inputs[i], false); + } + for (int i = 0; i < outputs.size(); ++i) { + TensorUtils::setTensorSupportPack(outputs[i], false); + } + + return new GroupNormBufExecution(op, backend); + } +}; + +REGISTER_OPENCL_OP_CREATOR(GroupNormBufCreator, OpType_GroupNorm, BUFFER); +} // namespace OpenCL +} // namespace MNN +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ +#endif/* MNN_OPENCL_BUFFER_CLOSED */ diff --git a/source/backend/opencl/execution/buffer/GroupNormBufExecution.hpp b/source/backend/opencl/execution/buffer/GroupNormBufExecution.hpp new file mode 100644 index 000000000..2f1ce8313 --- /dev/null +++ b/source/backend/opencl/execution/buffer/GroupNormBufExecution.hpp @@ -0,0 +1,45 @@ +// +// GroupNormBufExecution.hpp +// MNN +// +// Created by MNN on 2024/06/24. +// Copyright © 2018, Alibaba Group Holding Limited +// +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE + +#ifndef GroupNormBufExecution_hpp +#define GroupNormBufExecution_hpp + +#include "backend/opencl/execution/image/CommonExecution.hpp" + +namespace MNN { + +namespace OpenCL { +class GroupNormBufExecution : public CommonExecution { +public: + GroupNormBufExecution(const MNN::Op* op, Backend *backend); + virtual ~GroupNormBufExecution() = default; + + virtual ErrorCode onEncode(const std::vector &inputs, const std::vector &outputs) override; +private: + int getLocalSize(int size, int maxGroupSize); +private: + OpenCLBackend *mOpenCLBackend; + float mEpsilon{}; + int32_t mBSwish{}; + int32_t mGroup = 32; + int32_t mBatch; + std::unique_ptr mGammaTensor; + std::unique_ptr mBetaTensor; + std::shared_ptr mInputPlain, mOutputPlain; + bool mHasGammaBeta = false; + std::vector mLWS{0, 0, 0, 0}; + std::vector mGWS{0, 0, 0, 0}; +}; + +} // namespace OPENCL +} // namespace MNN +#endif /* GroupNormBufExecution_hpp */ +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ +#endif diff --git a/source/backend/opencl/execution/buffer/LoopBufExecution.cpp b/source/backend/opencl/execution/buffer/LoopBufExecution.cpp index 55a624f78..9935db7df 100644 --- a/source/backend/opencl/execution/buffer/LoopBufExecution.cpp +++ b/source/backend/opencl/execution/buffer/LoopBufExecution.cpp @@ -27,9 +27,19 @@ static void _TileOrPackTensor(Tensor *input, Tensor *output, std::shared_ptrgetOpenCLRuntime()->getGpuType() == GpuType::ADRENO) { buildOptions.emplace("-DUSE_CL_MAD=1"); @@ -530,47 +559,41 @@ ErrorCode LoopBatchMatMulBufExecution::onEncode(const std::vector &inp buildOptions.emplace(" -DPRECISION=32"); } - int localM = MDIMC; - int localN = NDIMC; + Unit unit; + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); + + int out_per_thread_m = tileM / localM; + int out_per_thread_n = tileN / localN; + + std::vector globalWorkSize = {static_cast(e_pack/out_per_thread_m), static_cast(h_pack/out_per_thread_n), static_cast(n)}; + std::vector localWorkSize = {static_cast(localM), static_cast(localN), 1}; + + float alpha = 1.0; + float beta = 0.0f; + + int idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, static_cast(e_pack)); + ret |= unit.kernel->get().setArg(idx++, static_cast(h_pack)); + ret |= unit.kernel->get().setArg(idx++, static_cast(l_pack)); + ret |= unit.kernel->get().setArg(idx++, alpha); + ret |= unit.kernel->get().setArg(idx++, beta); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mTmpTensors[1].get())); + ret |= unit.kernel->get().setArg(idx++, e_pack); + ret |= unit.kernel->get().setArg(idx++, l_pack); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mTmpTensors[2].get())); + ret |= unit.kernel->get().setArg(idx++, h_pack); + ret |= unit.kernel->get().setArg(idx++, l_pack); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mTmpTensors[0].get())); + ret |= unit.kernel->get().setArg(idx++, e_pack); + ret |= unit.kernel->get().setArg(idx++, h_pack); + MNN_CHECK_CL_SUCCESS(ret, "setArg LoopBuf GemmTile Kernel"); + + unit.globalWorkSize = {globalWorkSize[0], globalWorkSize[1], globalWorkSize[2]}; + unit.localWorkSize = {localWorkSize[0], localWorkSize[1], localWorkSize[2]}; + mUnits.emplace_back(unit); + mOpenCLBackend->recordKernel3d(unit.kernel, globalWorkSize, localWorkSize); - for(int b = 0; b < n; b++) { - Unit unit; - unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "Xgemm", buildOptions); - - int out_per_thread_m = tileM / localM; - int out_per_thread_n = tileN / localN; - - std::vector globalWorkSize = {static_cast(e_pack/out_per_thread_m), static_cast(h_pack/out_per_thread_n)}; - std::vector localWorkSize = {static_cast(localM), static_cast(localN)}; - - float alpha = 1.0; - float beta = 0.0f; - // A: [n, l, e] - // B: [n, l, h] - int offset_a = b * l_pack * e_pack; - int offset_b = b * l_pack * h_pack; - int offset_c = b * e_pack * h_pack; - - int idx = 0; - cl_int ret = CL_SUCCESS; - ret |= unit.kernel->get().setArg(idx++, static_cast(e_pack)); - ret |= unit.kernel->get().setArg(idx++, static_cast(h_pack)); - ret |= unit.kernel->get().setArg(idx++, static_cast(l_pack)); - ret |= unit.kernel->get().setArg(idx++, alpha); - ret |= unit.kernel->get().setArg(idx++, beta); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mTmpTensors[1].get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mTmpTensors[2].get())); - ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mTmpTensors[0].get())); - ret |= unit.kernel->get().setArg(idx++, offset_a); - ret |= unit.kernel->get().setArg(idx++, offset_b); - ret |= unit.kernel->get().setArg(idx++, offset_c); - MNN_CHECK_CL_SUCCESS(ret, "setArg LoopBuf GemmTile Kernel"); - - unit.globalWorkSize = {globalWorkSize[0], globalWorkSize[1]}; - unit.localWorkSize = {localWorkSize[0], localWorkSize[1]}; - mUnits.emplace_back(unit); - mOpenCLBackend->recordKernel2d(unit.kernel, globalWorkSize, localWorkSize); - } } else { // matmul mTmpTensors[0] = std::make_shared(Tensor::createDevice(std::vector{1, n, e, h}, Tensor::CAFFE)); @@ -701,7 +724,7 @@ ErrorCode LoopBatchMatMulBufExecution::onExecute(const std::vector &in std::string name = "While-gemm"; if(mBatchGemmOpt) { - if(idx <= mUnits.size()-2 && idx >= mUnits.size()-1-mBatch) { + if(idx == 2) { name += "-batchgemm"; } else if(idx == 0) { name += "-rearrangeA"; @@ -755,18 +778,16 @@ ErrorCode LoopBinaryBufExecution::onEncode(const std::vector &inputs, Unit unit; auto input0 = mTensors[cmd->indexes()->data()[1]]; - std::vector Input0Shape = tensorShapeFormat(input0); - int Input0Size[4] = {Input0Shape.at(2), Input0Shape.at(1),Input0Shape.at(3),Input0Shape.at(0)}; + std::vector input0C4Shape = tensorShapeFormat(input0); + int input0C4Size[4] = {input0C4Shape.at(0), input0C4Shape.at(3),input0C4Shape.at(1),input0C4Shape.at(2)}; auto input1 = mTensors[cmd->indexes()->data()[2]]; - std::vector Input1Shape = tensorShapeFormat(input1); - int Input1Size[4] = {Input1Shape.at(2), Input1Shape.at(1),Input1Shape.at(3),Input1Shape.at(0)}; + std::vector input1C4Shape = tensorShapeFormat(input1); + int input1C4Size[4] = {input1C4Shape.at(0), input1C4Shape.at(3),input1C4Shape.at(1),input1C4Shape.at(2)}; auto output = mTensors[cmd->indexes()->data()[0]]; - std::vector Shape = tensorShapeFormat(output); + std::vector outputC4Shape = tensorShapeFormat(output); - bool broadcastInput0 = false; - bool broadcastInput1 = false; int input0Shape[8] = {1, 1, 1, 1, 1, 1, 1, 1}; int input1Shape[8] = {1, 1, 1, 1, 1, 1, 1, 1}; int outputShape[8] = {1, 1, 1, 1, 1, 1, 1, 1}; @@ -831,25 +852,36 @@ ErrorCode LoopBinaryBufExecution::onEncode(const std::vector &inputs, if(input1->dimensions() > 4) { - for(int i = 4; i < input1->dimensions(); i++) + for(int i = 4; i < output->dimensions(); i++) { iC *= outputShape[i]; } } - input1Shape[0] = iN; + outputShape[0] = iN; outputShape[1] = iC; outputShape[2] = iH; outputShape[3] = iW; outputShape[4] = 1; } - - const int Channel = Shape.at(3); - const int Width = Shape.at(2); - const int Height = Shape.at(1); - const int Batch = Shape.at(0); - const int ChannelBlock = UP_DIV(Channel, 4); auto BuildOptions = mBuildOptions; + for(int i = 0; i < 4; ++i){ + if(input1C4Shape[i] != outputC4Shape[i]){ + BuildOptions.emplace("-DBROADCAST_INPUT1"); + break; + } + } + + const int Channel = outputC4Shape.at(3); + const int Width = outputC4Shape.at(2); + const int Height = outputC4Shape.at(1); + const int Batch = outputC4Shape.at(0); + const int ChannelBlock = UP_DIV(Channel, 4); std::string KernelName = "broadcast_binary_buf"; + if(input0Shape[1] == input1Shape[1] && input0C4Size[1] == input1C4Size[1]){ + KernelName = "broadcast_binary_channel_equall_buf"; + } else if((input0->dimensions() == 1 && input0Shape[1] == 1) || (input1->dimensions() == 1 && input1Shape[1] == 1)){ + KernelName = "broadcast_binary_dimmision1_channel1_buf"; + } unit.kernel = runTime->buildKernel("loop_buf", KernelName, BuildOptions, input0, output); uint32_t mMaxWorkGroupSize = static_cast(runTime->getMaxWorkGroupSize(unit.kernel)); @@ -864,9 +896,9 @@ ErrorCode LoopBinaryBufExecution::onEncode(const std::vector &inputs, ret |= unit.kernel->get().setArg(index++, openCLBuffer(input0)); ret |= unit.kernel->get().setArg(index++, openCLBuffer(input1)); ret |= unit.kernel->get().setArg(index++, sizeof(input0Shape), input0Shape); - ret |= unit.kernel->get().setArg(index++, sizeof(Input0Size), Input0Size); + ret |= unit.kernel->get().setArg(index++, sizeof(input0C4Size), input0C4Size); ret |= unit.kernel->get().setArg(index++, sizeof(input1Shape), input1Shape); - ret |= unit.kernel->get().setArg(index++, sizeof(Input1Size), Input1Size); + ret |= unit.kernel->get().setArg(index++, sizeof(input1C4Size), input1C4Size); ret |= unit.kernel->get().setArg(index++, sizeof(outputShape), outputShape); ret |= unit.kernel->get().setArg(index++, Width); ret |= unit.kernel->get().setArg(index++, Height); diff --git a/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp b/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp new file mode 100644 index 000000000..dc21fcb68 --- /dev/null +++ b/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.cpp @@ -0,0 +1,586 @@ +// +// FmhaV2Execution.cpp +// MNN +// +// Created by MNN on 2024/06/03. +// Copyright © 2018, Alibaba Group Holding Limited +// +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE + +#include +#include +#include "backend/opencl/execution/buffer/SelfAttentionBufExecution.hpp" + +namespace MNN { +namespace OpenCL { + +SelfAttentionBufImpl::SelfAttentionBufImpl(const MNN::Op *op, Backend *backend){ + auto fmha_v2_param = op->main_as_FmhaV2Param(); + mNumHead = fmha_v2_param->heads(); + mOpenCLBackend = static_cast(backend); + auto kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("self_attention_buf", "softmax_inside", {"-DSOFTMAX_LOCAL_SIZE=512"}); + mMaxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel)); +} + +int SelfAttentionBufImpl::getLocalSize(int size, int maxGroupSize){ + int local_size = 1; + while(local_size * 2 <= maxGroupSize && local_size * 2 <= size){ + local_size *= 2; + } + return local_size; +} +// [B, seqlen, HeadNum*3*HeadDim] -> [B, seqlen, HeadNum*HeadDim] +ErrorCode SelfAttentionBufImpl::onResize(Backend *backend, const std::vector &inputs, const std::vector &outputs) { + mOpenCLBackend = static_cast(backend); + mOpenCLBackend->startRecord(mRecording); + + auto input = inputs[0];// [Batch, seqLen, mNumHead * 3 * mHeadDim] + + auto runtime = mOpenCLBackend->getOpenCLRuntime(); + auto shape = input->shape(); + + int tile_mn = 32; + int tile_k = 16; // for gemm alignment + int batch = shape[0]; + int seq_len = shape[1]; + mHeadDim = shape[2] / mNumHead / 3; + mScale = 1.0 / sqrt(mHeadDim); + + if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ + mByte = 2; + } + + // split several pieces for memory save + if(seq_len > 1024) { + mQseqSplitNum = (seq_len >= 4096) ? 8 : ((seq_len < 2048) ? 2 : 4); + } + int buffer_size = batch * mNumHead * ROUND_UP(mHeadDim, tile_k) * ROUND_UP(seq_len, tile_mn); + int buffer_qk_size = batch * mNumHead * ROUND_UP(seq_len, tile_mn) * ROUND_UP(seq_len, tile_mn) / mQseqSplitNum; + int buffer_v_size = batch * mNumHead * ROUND_UP(mHeadDim, tile_mn) * ROUND_UP(seq_len, tile_mn); + mTempQ.reset(Tensor::createDevice(std::vector{buffer_size / mQseqSplitNum})); + mTempK.reset(Tensor::createDevice(std::vector{buffer_size})); + mTempV.reset(Tensor::createDevice(std::vector{buffer_v_size})); + mTempQK.reset(Tensor::createDevice(std::vector{buffer_qk_size})); + mTempTrans.reset(Tensor::createDevice(std::vector{buffer_qk_size})); + mTempSoftMax.reset(Tensor::createDevice(std::vector{buffer_qk_size})); + mTempQKV.reset(Tensor::createDevice(std::vector{buffer_v_size / mQseqSplitNum})); + +// printf("buffer size x2:%f MB, buffer qk size x3:%f MB, buffer v size x2 :%f MB\n", buffer_size * 2.0 / 1024.0 / 1024.0, buffer_qk_size * 2.0 / 1024.0 / 1024.0, buffer_v_size * 2.0 / 1024.0 / 1024.0); + mOpenCLBackend->onAcquireBuffer(mTempQ.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mTempK.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mTempV.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mTempQK.get(), Backend::DYNAMIC); + + mOpenCLBackend->onReleaseBuffer(mTempQ.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mTempK.get(), Backend::DYNAMIC); + + mOpenCLBackend->onAcquireBuffer(mTempSoftMax.get(), Backend::DYNAMIC); + + mOpenCLBackend->onReleaseBuffer(mTempQK.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mTempTrans.get(), Backend::DYNAMIC); + + mOpenCLBackend->onReleaseBuffer(mTempSoftMax.get(), Backend::DYNAMIC); + mOpenCLBackend->onAcquireBuffer(mTempQKV.get(), Backend::DYNAMIC); + + + mOpenCLBackend->onReleaseBuffer(mTempV.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mTempTrans.get(), Backend::DYNAMIC); + mOpenCLBackend->onReleaseBuffer(mTempQKV.get(), Backend::DYNAMIC); + + mKernel_split.resize(mQseqSplitNum); + mKernel_qk.resize(mQseqSplitNum); + mKernel_softmax.resize(mQseqSplitNum); + mKernel_qkv.resize(mQseqSplitNum); + mKernel_clip.resize(mQseqSplitNum); + mKernel_trans.resize(mQseqSplitNum); + mGlobalWorkSizeSplit.resize(mQseqSplitNum); + mLocalWorkSizeSplit.resize(mQseqSplitNum); + mGlobalWorkSizeClip.resize(mQseqSplitNum); + mLocalWorkSizeClip.resize(mQseqSplitNum); + mGlobalWorkSizeQk.resize(mQseqSplitNum); + mLocalWorkSizeQk.resize(mQseqSplitNum); + mGlobalWorkSizeSoftMax.resize(mQseqSplitNum); + mLocalWorkSizeSoftMax.resize(mQseqSplitNum); + mGlobalWorkSizeQkv.resize(mQseqSplitNum); + mLocalWorkSizeQkv.resize(mQseqSplitNum); + mGlobalWorkSizeTrans.resize(mQseqSplitNum); + mLocalWorkSizeTrans.resize(mQseqSplitNum); + + for(int seq_idx = 0; seq_idx < mQseqSplitNum; seq_idx++) { + // Split input to q k v + { + // [Batch, seqLen, mNumHead * 3 * mHeadDim] -> + // Q : [Batch * mNumHead, ROUND_UP(mHeadDim, tile_k), ROUND_UP(seqLen, tile_mn)] + // K : [Batch * mNumHead, ROUND_UP(mHeadDim, tile_k), ROUND_UP(seqLen, tile_mn)] + // V : [Batch * mNumHead, ROUND_UP(seqLen, tile_mn), ROUND_UP(mHeadDim, tile_mn)] + std::set buildOption; + if((mHeadDim % 4) != 0){ + buildOption.emplace("-DHEADDIM_LEAVE"); + } + if((seq_len % 4) != 0){ + buildOption.emplace("-DSEQLEN_LEAVE"); + } + + int seq_len_pack_mn = ROUND_UP(seq_len, tile_mn); + int head_dim_pack_mn = ROUND_UP(mHeadDim, tile_mn); + int head_dim_pack_k = ROUND_UP(mHeadDim, tile_k); + int seq_len_piece = seq_len_pack_mn/mQseqSplitNum; + + mKernel_split[seq_idx] = runtime->buildKernel("self_attention_buf", "split_transpose_qkv", buildOption, inputs[0], outputs[0]); + auto maxWorkGroupSize = static_cast(runtime->getMaxWorkGroupSize(mKernel_split[seq_idx])); + + mGlobalWorkSizeSplit[seq_idx] = {static_cast(UP_DIV(seq_len_pack_mn, 4)), static_cast(UP_DIV(head_dim_pack_mn, 4)), static_cast(batch*mNumHead)}; + + if(seq_idx > 0) { + mGlobalWorkSizeSplit[seq_idx][0] = static_cast(UP_DIV(seq_len_piece, 4)); + } + uint32_t index = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_split[seq_idx]->get().setArg(index++, mGlobalWorkSizeSplit[seq_idx][0]); + ret |= mKernel_split[seq_idx]->get().setArg(index++, mGlobalWorkSizeSplit[seq_idx][1]); + ret |= mKernel_split[seq_idx]->get().setArg(index++, mGlobalWorkSizeSplit[seq_idx][2]); + ret |= mKernel_split[seq_idx]->get().setArg(index++, openCLBuffer(input)); + ret |= mKernel_split[seq_idx]->get().setArg(index++, openCLBuffer(mTempQ.get())); + ret |= mKernel_split[seq_idx]->get().setArg(index++, openCLBuffer(mTempK.get())); + ret |= mKernel_split[seq_idx]->get().setArg(index++, openCLBuffer(mTempV.get())); + ret |= mKernel_split[seq_idx]->get().setArg(index++, seq_len_pack_mn); + ret |= mKernel_split[seq_idx]->get().setArg(index++, seq_len_piece); + ret |= mKernel_split[seq_idx]->get().setArg(index++, head_dim_pack_mn); + ret |= mKernel_split[seq_idx]->get().setArg(index++, head_dim_pack_k); + ret |= mKernel_split[seq_idx]->get().setArg(index++, seq_len); + ret |= mKernel_split[seq_idx]->get().setArg(index++, mNumHead); + ret |= mKernel_split[seq_idx]->get().setArg(index++, mHeadDim); + ret |= mKernel_split[seq_idx]->get().setArg(index++, seq_idx); + MNN_CHECK_CL_SUCCESS(ret, "setArg split_transpose_qkv"); + mLocalWorkSizeSplit[seq_idx] = localWS3DDefault(mGlobalWorkSizeSplit[seq_idx], maxWorkGroupSize, runtime, "split_transpose_qkv", mKernel_split[seq_idx]).first; + + mOpenCLBackend->recordKernel3d(mKernel_split[seq_idx], mGlobalWorkSizeSplit[seq_idx], mLocalWorkSizeSplit[seq_idx]); + } + + // query * key -> div + { + // Q : [Batch * mNumHead, ROUND_UP(mHeadDim, tile_k), ROUND_UP(seqLen, tile_mn)] -> [B, K, M] + // K : [Batch * mNumHead, ROUND_UP(mHeadDim, tile_k), ROUND_UP(seqLen, tile_mn)] -> [B, K, N] + // QV: [Batch * mNumHead, ROUND_UP(seqLen, tile_mn), ROUND_UP(seqLen, tile_mn)] -> [B, N, M] + int loop = batch * mNumHead; + int e_pack = ROUND_UP(seq_len, tile_mn) / mQseqSplitNum; + int l_pack = ROUND_UP(mHeadDim, tile_k); + int h_pack = ROUND_UP(seq_len, tile_mn); + + std::set buildOptions; + + uint32_t layout = 4; + auto param = getGemmParams({(uint32_t)e_pack, (uint32_t)h_pack, (uint32_t)l_pack, layout, (uint32_t)loop}, {openCLBuffer(mTempQ.get()), openCLBuffer(mTempK.get()), openCLBuffer(mTempQK.get())}, mOpenCLBackend->getOpenCLRuntime()); + + int GEMMK=param[0], KREG=param[1], KWG=param[2], KWI=param[3], MDIMA=param[4], MDIMC=param[5], MWG=param[6], NDIMB=param[7], NDIMC=param[8], NWG=param[9], SA=param[10], SB=param[11], STRM=param[12], STRN=param[13], VWM=param[14], VWN=param[15]; + buildOptions.emplace("-DGEMMK=" + std::to_string(GEMMK)); + buildOptions.emplace("-DKREG=" + std::to_string(KREG)); + buildOptions.emplace("-DKWG=" + std::to_string(KWG)); + buildOptions.emplace("-DKWI=" + std::to_string(KWI)); + buildOptions.emplace("-DMDIMA=" + std::to_string(MDIMA)); + buildOptions.emplace("-DMDIMC=" + std::to_string(MDIMC)); + buildOptions.emplace("-DMWG=" + std::to_string(MWG)); + buildOptions.emplace("-DNDIMB=" + std::to_string(NDIMB)); + buildOptions.emplace("-DNDIMC=" + std::to_string(NDIMC)); + buildOptions.emplace("-DNWG=" + std::to_string(NWG)); + buildOptions.emplace("-DSA=" + std::to_string(SA)); + buildOptions.emplace("-DSB=" + std::to_string(SB)); + buildOptions.emplace("-DSTRM=" + std::to_string(STRM)); + buildOptions.emplace("-DSTRN=" + std::to_string(STRN)); + buildOptions.emplace("-DVWM=" + std::to_string(VWM)); + buildOptions.emplace("-DVWN=" + std::to_string(VWN)); + if(layout >= 4) { + buildOptions.emplace("-DOUTPUTMN"); + } + + int tileM = MWG; + int tileN = NWG; + int localM = MDIMC; + int localN = NDIMC; + + if(mOpenCLBackend->getOpenCLRuntime()->getGpuType() == GpuType::ADRENO) { + buildOptions.emplace("-DUSE_CL_MAD=1"); + buildOptions.emplace("-DRELAX_WORKGROUP_SIZE=1"); + } + + if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ + buildOptions.emplace(" -DPRECISION=16"); + } else { + buildOptions.emplace(" -DPRECISION=32"); + } + + mKernel_qk[seq_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); + + int out_per_thread_m = tileM / localM; + int out_per_thread_n = tileN / localN; + + mGlobalWorkSizeQk[seq_idx] = {static_cast(e_pack/out_per_thread_m), static_cast(h_pack/out_per_thread_n), static_cast(loop)}; + mLocalWorkSizeQk[seq_idx] = {static_cast(localM), static_cast(localN), 1}; + + float alpha = mScale; + float beta = 0.0f; + + int idx = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, static_cast(e_pack)); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, static_cast(h_pack)); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, static_cast(l_pack)); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, alpha); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, beta); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, openCLBuffer(mTempQ.get())); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, e_pack); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, l_pack); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, openCLBuffer(mTempK.get())); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, h_pack); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, l_pack); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, openCLBuffer(mTempQK.get())); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, e_pack); + ret |= mKernel_qk[seq_idx]->get().setArg(idx++, h_pack); + MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention batchmatmul qk Kernel"); + mOpenCLBackend->recordKernel3d(mKernel_qk[seq_idx], mGlobalWorkSizeQk[seq_idx], mLocalWorkSizeQk[seq_idx]); + + } + + // softmax + { + // QV: [Batch * mNumHead, ROUND_UP(seqLen, tile_mn), ROUND_UP(seqLen, tile_mn)] + // Sotmax: [Batch * mNumHead, ROUND_UP(seqLen, tile_mn), ROUND_UP(seqLen, tile_mn)] + // axis : 1 (middle dim) + mSoftmaxShape[0] = batch*mNumHead; + mSoftmaxShape[1] = ROUND_UP(seq_len, tile_mn)/mQseqSplitNum; + mSoftmaxShape[2] = ROUND_UP(seq_len, tile_mn); + + auto MaxLocalSize = std::min(std::min(runtime->getMaxWorkItemSizes()[0], mMaxWorkGroupSize), static_cast(256)); + int localSize = getLocalSize(mSoftmaxShape[1], MaxLocalSize); + if(localSize < 4){ + localSize = 1; + } + + std::set buildOption; + buildOption.emplace("-DSOFTMAX_LOCAL_SIZE=" + std::to_string(localSize)); + // buildOption.emplace("-DOUTPUT_TRANSPOSE"); + + mKernel_softmax[seq_idx] = runtime->buildKernel("self_attention_buf", "softmax_inside", buildOption, inputs[0], outputs[0]); + mGlobalWorkSizeSoftMax[seq_idx] = {static_cast(localSize), static_cast(mSoftmaxShape[1]), static_cast(mSoftmaxShape[0])}; + + uint32_t index = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, mGlobalWorkSizeSoftMax[seq_idx][0]); + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, mGlobalWorkSizeSoftMax[seq_idx][1]); + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, mGlobalWorkSizeSoftMax[seq_idx][2]); + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, openCLBuffer(mTempQK.get())); + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, seq_len); + ret |= mKernel_softmax[seq_idx]->get().setArg(index++, mSoftmaxShape); + MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention softmax"); + + mLocalWorkSizeSoftMax[seq_idx] = {static_cast(localSize), 1, 1}; + mOpenCLBackend->recordKernel3d(mKernel_softmax[seq_idx], mGlobalWorkSizeSoftMax[seq_idx], mLocalWorkSizeSoftMax[seq_idx]); + } + + { + unsigned int tileW = 32; + unsigned int tileH = 32; + int loop = batch * mNumHead; + int transDimW = ROUND_UP(seq_len, tile_mn) / mQseqSplitNum; + int transDimH = ROUND_UP(seq_len, tile_mn); + if((transDimW & 63) == 0 && (transDimH & 63) == 0) { + tileW = 64; + tileH = 64; + } + unsigned int localW = 8; + unsigned int localH = 8; + std::set buildOptions; + buildOptions.emplace("-DWGSW=" + std::to_string(tileW)); + buildOptions.emplace("-DWGSH=" + std::to_string(tileH)); + buildOptions.emplace("-DTSW=" + std::to_string(tileW/localW)); + buildOptions.emplace("-DTSH=" + std::to_string(tileH/localH)); + + mKernel_trans[seq_idx] = runtime->buildKernel("self_attention_buf", "trans_3d_buf", buildOptions, inputs[0], outputs[0]); + + int w_per_thread = tileW / localW; + int h_per_thread = tileH / localH; + mGlobalWorkSizeTrans[seq_idx] = {(uint32_t)transDimW/w_per_thread, (uint32_t)transDimH/h_per_thread, (uint32_t)(loop)}; + mLocalWorkSizeTrans[seq_idx] = {localW, localH, 1}; + + uint32_t index = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_trans[seq_idx]->get().setArg(index++, openCLBuffer(mTempSoftMax.get())); + ret |= mKernel_trans[seq_idx]->get().setArg(index++, openCLBuffer(mTempTrans.get())); + ret |= mKernel_trans[seq_idx]->get().setArg(index++, loop); + ret |= mKernel_trans[seq_idx]->get().setArg(index++, transDimW); + ret |= mKernel_trans[seq_idx]->get().setArg(index++, transDimH); + MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention transpose"); + + mOpenCLBackend->recordKernel3d(mKernel_trans[seq_idx], mGlobalWorkSizeTrans[seq_idx], mLocalWorkSizeTrans[seq_idx]); + } + + + // qk * value + { + // Sotmax: [Batch * mNumHead, ROUND_UP(seqLen, tile), ROUND_UP(seqLen, tile)] -> [B, K, M] + // V : [Batch * mNumHead, ROUND_UP(seqLen, tile), ROUND_UP(mHeadDim, tile)] -> [B, K, N] + // QKV : [Batch * mNumHead, ROUND_UP(mHeadDim, tile), ROUND_UP(seqLen, tile)] -> [B, N, M] + + int loop = batch * mNumHead; + int e_pack = ROUND_UP(seq_len, tile_mn) / mQseqSplitNum; + int l_pack = ROUND_UP(seq_len, tile_mn); + int h_pack = ROUND_UP(mHeadDim, tile_mn); + + std::set buildOptions; + /* + 0 -> A:[K, M] B:[K, N] C:[N, M] + 1 -> A:[K, M] B:[N, K] C:[N, M] + 2 -> A:[M, K] B:[K, N] C:[N, M] + 3 -> A:[M, K] B:[N, K] C:[N, M] + 4 -> A:[K, M] B:[K, N] C:[M, N] + 5 -> A:[K, M] B:[N, K] C:[M, N] + 6 -> A:[M, K] B:[K, N] C:[M, N] + 7 -> A:[M, K] B:[N, K] C:[M, N] + */ + uint32_t layout = 0; + auto param = getGemmParams({(uint32_t)e_pack, (uint32_t)h_pack, (uint32_t)l_pack, layout, (uint32_t)loop}, {openCLBuffer(mTempTrans.get()), openCLBuffer(mTempV.get()), openCLBuffer(mTempQKV.get())}, mOpenCLBackend->getOpenCLRuntime()); + + int GEMMK=param[0], KREG=param[1], KWG=param[2], KWI=param[3], MDIMA=param[4], MDIMC=param[5], MWG=param[6], NDIMB=param[7], NDIMC=param[8], NWG=param[9], SA=param[10], SB=param[11], STRM=param[12], STRN=param[13], VWM=param[14], VWN=param[15]; + buildOptions.emplace("-DGEMMK=" + std::to_string(GEMMK)); + buildOptions.emplace("-DKREG=" + std::to_string(KREG)); + buildOptions.emplace("-DKWG=" + std::to_string(KWG)); + buildOptions.emplace("-DKWI=" + std::to_string(KWI)); + buildOptions.emplace("-DMDIMA=" + std::to_string(MDIMA)); + buildOptions.emplace("-DMDIMC=" + std::to_string(MDIMC)); + buildOptions.emplace("-DMWG=" + std::to_string(MWG)); + buildOptions.emplace("-DNDIMB=" + std::to_string(NDIMB)); + buildOptions.emplace("-DNDIMC=" + std::to_string(NDIMC)); + buildOptions.emplace("-DNWG=" + std::to_string(NWG)); + buildOptions.emplace("-DSA=" + std::to_string(SA)); + buildOptions.emplace("-DSB=" + std::to_string(SB)); + buildOptions.emplace("-DSTRM=" + std::to_string(STRM)); + buildOptions.emplace("-DSTRN=" + std::to_string(STRN)); + buildOptions.emplace("-DVWM=" + std::to_string(VWM)); + buildOptions.emplace("-DVWN=" + std::to_string(VWN)); + if(layout >= 4) { + buildOptions.emplace("-DOUTPUTMN"); + } + + int tileM = MWG; + int tileN = NWG; + int localM = MDIMC; + int localN = NDIMC; + + if(mOpenCLBackend->getOpenCLRuntime()->getGpuType() == GpuType::ADRENO) { + buildOptions.emplace("-DUSE_CL_MAD=1"); + buildOptions.emplace("-DRELAX_WORKGROUP_SIZE=1"); + } + + if(mOpenCLBackend->getOpenCLRuntime()->isSupportedFP16()){ + buildOptions.emplace(" -DPRECISION=16"); + } else { + buildOptions.emplace(" -DPRECISION=32"); + } + + mKernel_qkv[seq_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("matmul_params_buf", "XgemmBatched", buildOptions); + + int out_per_thread_m = tileM / localM; + int out_per_thread_n = tileN / localN; + + mGlobalWorkSizeQkv[seq_idx] = {static_cast(e_pack/out_per_thread_m), static_cast(h_pack/out_per_thread_n), static_cast(loop)}; + mLocalWorkSizeQkv[seq_idx] = {static_cast(localM), static_cast(localN), 1}; + + float alpha = 1.0f; + float beta = 0.0f; + + int idx = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, static_cast(e_pack)); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, static_cast(h_pack)); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, static_cast(l_pack)); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, alpha); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, beta); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, openCLBuffer(mTempTrans.get())); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, e_pack); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, l_pack); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, openCLBuffer(mTempV.get())); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, h_pack); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, l_pack); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, openCLBuffer(mTempQKV.get())); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, e_pack); + ret |= mKernel_qkv[seq_idx]->get().setArg(idx++, h_pack); + MNN_CHECK_CL_SUCCESS(ret, "setArg Self-Attention batchmatmul qkv Kernel"); + mOpenCLBackend->recordKernel3d(mKernel_qkv[seq_idx], mGlobalWorkSizeQkv[seq_idx], mLocalWorkSizeQkv[seq_idx]); + } + + // transpose to output + { + // QKV : [Batch * mNumHead, ROUND_UP(mHeadDim, tile_mn), ROUND_UP(seqLen, tile_mn)] -> [B, N, M] + // output: [Batch, seqLen, mNumHead * mHeadDim] + std::set buildOption; + + mKernel_clip[seq_idx] = runtime->buildKernel("self_attention_buf", "clip_transpose_qkv", buildOption, inputs[0], outputs[0]); + auto maxWorkGroupSize = static_cast(runtime->getMaxWorkGroupSize(mKernel_clip[seq_idx])); + + int seq_len_piece = ROUND_UP(seq_len, tile_mn) / mQseqSplitNum; + + mGlobalWorkSizeClip[seq_idx] = {static_cast(UP_DIV(seq_len_piece, 4)), static_cast(UP_DIV(mHeadDim, 4)), static_cast(batch*mNumHead)}; + + uint32_t index = 0; + cl_int ret = CL_SUCCESS; + ret |= mKernel_clip[seq_idx]->get().setArg(index++, mGlobalWorkSizeClip[seq_idx][0]); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, mGlobalWorkSizeClip[seq_idx][1]); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, mGlobalWorkSizeClip[seq_idx][2]); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, openCLBuffer(mTempQKV.get())); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, openCLBuffer(outputs[0])); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, tile_mn); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, seq_len); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, seq_len_piece); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, mNumHead); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, mHeadDim); + ret |= mKernel_clip[seq_idx]->get().setArg(index++, seq_idx); + + mLocalWorkSizeClip[seq_idx] = localWS3DDefault(mGlobalWorkSizeClip[seq_idx], maxWorkGroupSize, runtime, "clip_transpose_qkv", mKernel_clip[seq_idx]).first; + MNN_CHECK_CL_SUCCESS(ret, "setArg clip_transpose_qkv"); + mOpenCLBackend->recordKernel3d(mKernel_clip[seq_idx], mGlobalWorkSizeClip[seq_idx], mLocalWorkSizeClip[seq_idx]); + } + } + mOpenCLBackend->endRecord(mRecording); + return NO_ERROR; +} + +ErrorCode SelfAttentionBufImpl::onExecute(Backend *backend, const std::vector &inputs, const std::vector &outputs) { +#ifdef LOG_VERBOSE + MNN_PRINT("start SelfAttentionBufExecution onExecute !\n"); +#endif + mOpenCLBackend = static_cast(backend); +#ifdef ENABLE_OPENCL_TIME_PROFILER + int batch = inputs[0]->shape()[0]; + int seqLen = inputs[0]->shape()[1]; + int headDim = inputs[0]->shape()[2]/3/mNumHead; + + std::string name; + name += "-b" + std::to_string(batch); + name += "-s" + std::to_string(seqLen); + name += "-h" + std::to_string(mNumHead); + name += "-d" + std::to_string(headDim); + + for(int seq_idx = 0; seq_idx < mQseqSplitNum; seq_idx++) { + { + cl::Event event; + run3DKernelDefault(mKernel_split[seq_idx], mGlobalWorkSizeSplit[seq_idx], mLocalWorkSizeSplit[seq_idx], + mOpenCLBackend->getOpenCLRuntime(), &event); + + mOpenCLBackend->getOpenCLRuntime()->pushEvent({"While-gemm-split" + name, event}); + } + { + cl::Event event; + run3DKernelDefault(mKernel_qk[seq_idx], mGlobalWorkSizeQk[seq_idx], mLocalWorkSizeQk[seq_idx], + mOpenCLBackend->getOpenCLRuntime(), &event); + + mOpenCLBackend->getOpenCLRuntime()->pushEvent({"While-gemm-batchgemm" + name, event}); + } + { + cl::Event event; + run3DKernelDefault(mKernel_softmax[seq_idx], mGlobalWorkSizeSoftMax[seq_idx], mLocalWorkSizeSoftMax[seq_idx], + mOpenCLBackend->getOpenCLRuntime(), &event); + + mOpenCLBackend->getOpenCLRuntime()->pushEvent({"While-gemm-softmax" + name, event}); + } + { + cl::Event event; + run3DKernelDefault(mKernel_trans[seq_idx], mGlobalWorkSizeTrans[seq_idx], mLocalWorkSizeTrans[seq_idx], mOpenCLBackend->getOpenCLRuntime(), &event); + mOpenCLBackend->getOpenCLRuntime()->pushEvent({"While-gemm-trans-1" + name, event}); + } + { + cl::Event event; + run3DKernelDefault(mKernel_qkv[seq_idx], mGlobalWorkSizeQkv[seq_idx], mLocalWorkSizeQkv[seq_idx], + mOpenCLBackend->getOpenCLRuntime(), &event); + + mOpenCLBackend->getOpenCLRuntime()->pushEvent({"While-gemm-batchgemm" + name, event}); + } + { + cl::Event event; + run3DKernelDefault(mKernel_clip[seq_idx], mGlobalWorkSizeClip[seq_idx], mLocalWorkSizeClip[seq_idx], + mOpenCLBackend->getOpenCLRuntime(), &event); + + mOpenCLBackend->getOpenCLRuntime()->pushEvent({"While-gemm-clip" + name, event}); + } + } +#else + for(int seq_idx = 0; seq_idx < mQseqSplitNum; seq_idx++) { + run3DKernelDefault(mKernel_split[seq_idx], mGlobalWorkSizeSplit[seq_idx], mLocalWorkSizeSplit[seq_idx], mOpenCLBackend->getOpenCLRuntime()); + run3DKernelDefault(mKernel_qk[seq_idx], mGlobalWorkSizeQk[seq_idx], mLocalWorkSizeQk[seq_idx], mOpenCLBackend->getOpenCLRuntime()); + run3DKernelDefault(mKernel_softmax[seq_idx], mGlobalWorkSizeSoftMax[seq_idx], mLocalWorkSizeSoftMax[seq_idx], mOpenCLBackend->getOpenCLRuntime()); + + run3DKernelDefault(mKernel_trans[seq_idx], mGlobalWorkSizeTrans[seq_idx], mLocalWorkSizeTrans[seq_idx], mOpenCLBackend->getOpenCLRuntime()); + run3DKernelDefault(mKernel_qkv[seq_idx], mGlobalWorkSizeQkv[seq_idx], mLocalWorkSizeQkv[seq_idx], mOpenCLBackend->getOpenCLRuntime()); + run3DKernelDefault(mKernel_clip[seq_idx], mGlobalWorkSizeClip[seq_idx], mLocalWorkSizeClip[seq_idx], mOpenCLBackend->getOpenCLRuntime()); + + #ifdef DUMP_INTERNAL_LOG + { + std::ofstream outFile("qk.txt"); + std::vector hostPtr_3(16*4096*4096); + mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueReadBuffer(openCLBuffer(mTempQK.get()), CL_TRUE, 0, 16*4096*4096*4, hostPtr_3.data()); + float max_ = -1000000.0; + float min_ = 10000000.0; + float total = 0.0; + for(int i=1; i temp) min_ = temp; + } + outFile.close(); + printf("qk max:%f min:%f avg:%f\n", max_, min_, hostPtr_3[0]+total); + } + #endif + } +#endif + +#ifdef LOG_VERBOSE + MNN_PRINT("end SelfAttentionBufExecution onExecute !\n"); +#endif + + return NO_ERROR; +} + +SelfAttentionBufExecution::SelfAttentionBufExecution(const MNN::Op *op, Backend* backend) : CommonExecution(backend, op) { + mImpl.reset(new SelfAttentionBufImpl(op, backend)); +} + +SelfAttentionBufExecution::SelfAttentionBufExecution(std::shared_ptr impl, const MNN::Op *op, Backend *backend) : CommonExecution(backend, op), mImpl(impl) {} + +ErrorCode SelfAttentionBufExecution::onResize(const std::vector& inputs, const std::vector& outputs) { + return mImpl->onResize(backend(), inputs, outputs); +} + +ErrorCode SelfAttentionBufExecution::onExecute(const std::vector& inputs, const std::vector& outputs) { + return mImpl->onExecute(backend(), inputs, outputs); +} + +bool SelfAttentionBufExecution::onClone(Backend* bn, const Op* op, Execution** dst) { + if (nullptr == dst) { + return true; + } + *dst = new SelfAttentionBufExecution(mImpl, op, bn); + return true; +} + +class SelfAttentionBufCreator : public OpenCLBackend::Creator { +public: + virtual Execution *onCreate(const std::vector &inputs, const std::vector &outputs, + const MNN::Op *op, Backend *backend) const override { + for (int i = 0; i < inputs.size(); ++i) { + TensorUtils::setTensorSupportPack(inputs[i], false); + } + for (int i = 0; i < outputs.size(); ++i) { + TensorUtils::setTensorSupportPack(outputs[i], false); + } + return new SelfAttentionBufExecution(op, backend); + } +}; +REGISTER_OPENCL_OP_CREATOR(SelfAttentionBufCreator, OpType_FmhaV2, BUFFER); + +} // namespace OpenCL +} // namespace MNN +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ +#endif/* MNN_OPENCL_BUFFER_CLOSED */ diff --git a/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.hpp b/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.hpp new file mode 100644 index 000000000..31786f666 --- /dev/null +++ b/source/backend/opencl/execution/buffer/SelfAttentionBufExecution.hpp @@ -0,0 +1,79 @@ +// +// FmhaV2Execution.hpp +// MNN +// +// Created by MNN on 2024/06/03. +// Copyright © 2018, Alibaba Group Holding Limited +// +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE + +#ifndef SelfAttentionBufExecution_hpp +#define SelfAttentionBufExecution_hpp + +#include "backend/opencl/execution/image/CommonExecution.hpp" + +namespace MNN { +namespace OpenCL { + +class SelfAttentionBufImpl { +public: + SelfAttentionBufImpl(const MNN::Op *op, Backend *backend); + + ~SelfAttentionBufImpl() = default; + ErrorCode onResize(Backend *backend, const std::vector &inputs, const std::vector &outputs); + ErrorCode onExecute(Backend *backend, const std::vector &inputs, const std::vector &outputs); + +private: + int getLocalSize(int size, int maxGroupSize); + float mScale; + int mQseqSplitNum = 1; + std::shared_ptr mTempQ, mTempK, mTempQK, mTempSoftMax, mTempV, mTempQKV; + std::shared_ptr mTempTrans; + int mNumHead = 0, mHeadDim = 0; + std::vector> mKernel_split; + std::vector> mKernel_qk; + std::vector> mKernel_softmax; + std::vector> mKernel_qkv; + std::vector> mKernel_clip; + std::vector> mKernel_trans; + std::vector> mGlobalWorkSizeSplit; + std::vector> mLocalWorkSizeSplit; + std::vector> mGlobalWorkSizeClip; + std::vector> mLocalWorkSizeClip; + std::vector> mGlobalWorkSizeQk; + std::vector> mLocalWorkSizeQk; + std::vector> mGlobalWorkSizeSoftMax; + std::vector> mLocalWorkSizeSoftMax; + std::vector> mGlobalWorkSizeQkv; + std::vector> mLocalWorkSizeQkv; + std::vector> mGlobalWorkSizeTrans; + std::vector> mLocalWorkSizeTrans; + uint32_t mMaxWorkGroupSize; + OpenCLBackend *mOpenCLBackend; + size_t mQkGlobal_size[3]; + int mSoftmaxShape[4]; + int mByte = 4; + cl_recording_qcom mRecording{NULL}; + +}; + +class SelfAttentionBufExecution : public CommonExecution { +public: + SelfAttentionBufExecution(const MNN::Op *op, Backend *backend); + SelfAttentionBufExecution(std::shared_ptr impl, const MNN::Op *op, Backend *backend); + + virtual ~SelfAttentionBufExecution() = default; + virtual ErrorCode onResize(const std::vector &inputs, const std::vector &outputs) override; + virtual ErrorCode onExecute(const std::vector &inputs, const std::vector &outputs) override; + virtual bool onClone(Backend* bn, const Op* op, Execution** dst) override; + +private: + std::shared_ptr mImpl; +}; +} // namespace OpenCL +} // namespace MNN +#endif /* SelfAttentionBufExecution_hpp */ +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ + +#endif /* MNN_OPENCL_BUFFER_CLOSED */ diff --git a/source/backend/opencl/execution/buffer/SplitGeluBufExecution.cpp b/source/backend/opencl/execution/buffer/SplitGeluBufExecution.cpp new file mode 100644 index 000000000..171ee58a1 --- /dev/null +++ b/source/backend/opencl/execution/buffer/SplitGeluBufExecution.cpp @@ -0,0 +1,103 @@ + +// +// SplitGeluBufExecution.cpp +// MNN +// +// Created by MNN on 2024/06/26. +// Copyright © 2018, Alibaba Group Holding Limited +// +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE + +#include "backend/opencl/execution/buffer/SplitGeluBufExecution.hpp" + +namespace MNN { +namespace OpenCL { + +SplitGeluBufExecution::SplitGeluBufExecution(const MNN::Op* op, Backend* backend) : CommonExecution(backend, op) { + mOpenCLBackend = static_cast(backend); +} + +ErrorCode SplitGeluBufExecution::onEncode(const std::vector& inputs, const std::vector& outputs) { + auto runtime = static_cast(backend())->getOpenCLRuntime(); + + MNN_ASSERT(outputs.size() == 1); + auto input = inputs[0]; + auto output = outputs[0]; + MNN_ASSERT(input->dimensions() == 3); + MNN_ASSERT(output->dimensions() == 3); + if(inputs.size() > 1) { + MNN_ASSERT(inputs[1]->dimensions() == 1); + MNN_ASSERT(inputs[1]->length(0) == inputs[0]->length(2)); + } + + mUnits.clear(); + mUnits.resize(1); + std::vector outputShape = tensorShapeFormat(output); + int shape[4] = {outputShape[0], outputShape[3], outputShape[1], outputShape[2]}; + std::set buildOptions; + if(inputs.size() > 1) { + buildOptions.emplace("-DDOUBLE_INPUTS"); + } + int pack_wh = 1; + if(shape[2] % 4 == 0) { + pack_wh = 4; + buildOptions.emplace("-DWH_4"); + } + auto &unit = mUnits[0]; + std::string kernelName = "splitgelu_buf"; + unit.kernel = runtime->buildKernel("splitgelu_buf", kernelName, buildOptions); + + auto maxWorkGroupSize = static_cast(runtime->getMaxWorkGroupSize(unit.kernel)); + + mGWS = {static_cast(shape[0]), + static_cast(UP_DIV(shape[1], 4)), + static_cast(UP_DIV(shape[2],pack_wh))}; + + uint32_t idx = 0; + cl_int ret = CL_SUCCESS; + ret |= unit.kernel->get().setArg(idx++, mGWS[0]); + ret |= unit.kernel->get().setArg(idx++, mGWS[1]); + ret |= unit.kernel->get().setArg(idx++, mGWS[2]); + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(input)); + if(inputs.size() > 1) { + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(inputs[1])); + } + ret |= unit.kernel->get().setArg(idx++, openCLBuffer(output)); + ret |= unit.kernel->get().setArg(idx++, sizeof(shape), shape); + + MNN_CHECK_CL_SUCCESS(ret, "setArg SplitGeluBufExecution"); + + mLWS = localWS3DDefault(mGWS, maxWorkGroupSize, runtime, "splitgelu_buf", unit.kernel).first; + + unit.globalWorkSize = {mGWS[0], mGWS[1], mGWS[2]}; + unit.localWorkSize = {mLWS[0], mLWS[1], mLWS[2]}; + + mOpenCLBackend->recordKernel3d(unit.kernel, mGWS, mLWS); + mOpenCLBackend->endRecord(mRecording); + return NO_ERROR; + +} + + +class SplitGeluBufCreator : public OpenCLBackend::Creator { +public: + virtual ~SplitGeluBufCreator() = default; + virtual Execution *onCreate(const std::vector &inputs, const std::vector &outputs, + const MNN::Op *op, Backend *backend) const override { + for (int i = 0; i < inputs.size(); ++i) { + TensorUtils::setTensorSupportPack(inputs[i], false); + } + for (int i = 0; i < outputs.size(); ++i) { + TensorUtils::setTensorSupportPack(outputs[i], false); + } + + return new SplitGeluBufExecution(op, backend); + } +}; + +REGISTER_OPENCL_OP_CREATOR(SplitGeluBufCreator, OpType_SplitGeLU, BUFFER); +} // namespace OpenCL +} // namespace MNN +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ +#endif/* MNN_OPENCL_BUFFER_CLOSED */ diff --git a/source/backend/opencl/execution/buffer/SplitGeluBufExecution.hpp b/source/backend/opencl/execution/buffer/SplitGeluBufExecution.hpp new file mode 100644 index 000000000..9ecd65b8b --- /dev/null +++ b/source/backend/opencl/execution/buffer/SplitGeluBufExecution.hpp @@ -0,0 +1,39 @@ +// +// SplitGeluBufExecution.hpp +// MNN +// +// Created by MNN on 2024/06/26. +// Copyright © 2018, Alibaba Group Holding Limited +// +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_TRANSFORMER_FUSE + +#ifndef SplitGeluBufExecution_hpp +#define SplitGeluBufExecution_hpp + +#include "backend/opencl/execution/image/CommonExecution.hpp" + +namespace MNN { + +namespace OpenCL { +class SplitGeluBufExecution : public CommonExecution { +public: + SplitGeluBufExecution(const MNN::Op* op, Backend *backend); + virtual ~SplitGeluBufExecution() = default; + + virtual ErrorCode onEncode(const std::vector &inputs, const std::vector &outputs) override; + +private: + OpenCLBackend *mOpenCLBackend; + float mFDiv{}; + float mFAdd{}; + float mFMul{}; + std::vector mLWS{0, 0, 0, 0}; + std::vector mGWS{0, 0, 0, 0}; +}; + +} // namespace OPENCL +} // namespace MNN +#endif /* SplitGeluBufExecution_hpp */ +#endif/* MNN_SUPPORT_TRANSFORMER_FUSE */ +#endif diff --git a/source/backend/opencl/execution/cl/argmax_buf.cl b/source/backend/opencl/execution/cl/argmax_buf.cl index 48b2b3acc..5240eea4e 100644 --- a/source/backend/opencl/execution/cl/argmax_buf.cl +++ b/source/backend/opencl/execution/cl/argmax_buf.cl @@ -14,13 +14,13 @@ __private const int global_size_dim0, __private const int global_size_dim1, __pr if(A.x < B.x){ A.x = B.x; C.x = D; } \ if(A.y < B.y){ A.y = B.y; C.y = D; } \ if(A.z < B.z){ A.z = B.z; C.z = D; } \ - if(A.w < B.w){ A.w = B.w; C.w = D; } \ + if(A.w < B.w){ A.w = B.w; C.w = D; } #define ARGMIN_SELECT(A, B, C, D) \ if(A.x > B.x){ A.x = B.x; C.x = D; } \ if(A.y > B.y){ A.y = B.y; C.y = D; } \ if(A.z > B.z){ A.z = B.z; C.z = D; } \ - if(A.w > B.w){ A.w = B.w; C.w = D; } \ + if(A.w > B.w){ A.w = B.w; C.w = D; } __kernel void argmax_width_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT* input, diff --git a/source/backend/opencl/execution/cl/attention_buf.cl b/source/backend/opencl/execution/cl/attention_buf.cl index a1f6f9113..c17be5a4f 100644 --- a/source/backend/opencl/execution/cl/attention_buf.cl +++ b/source/backend/opencl/execution/cl/attention_buf.cl @@ -15,7 +15,7 @@ __kernel void matmul_qk_div_mask(GLOBAL_SIZE_3_DIMS __global const FLOAT *input0, // query [1 query_seq_len/4 head_num head_dim 4] __global const FLOAT *input1, // key [1 key_seq_len/4 head_num head_dim 4] __global FLOAT *output, // prefill [1 head_num query_seq_len/4 key_seq_len 4] decode[1 head_num key_seq_len/4 4] - __global FLOAT *past_key, // [1 key_seq_len/4 head_num head_dim 4] + __global FLOAT *past_key, // [1 head_num max_length/4 head_dim 4] #ifdef ADD_MASK __global const FLOAT* mask, #else @@ -25,6 +25,7 @@ __kernel void matmul_qk_div_mask(GLOBAL_SIZE_3_DIMS __private const int query_seq_len, __private const int key_seq_len, __private const int head_num, + __private const int kv_head_num, __private const int head_dim) { const int x = get_global_id(0); // query_seq_len / 4 for prefill 1 for decode @@ -32,85 +33,86 @@ __kernel void matmul_qk_div_mask(GLOBAL_SIZE_3_DIMS const int z = get_global_id(2); // key_seq_len / 4 DEAL_NON_UNIFORM_DIM3(x, y, z); + int yin = y / NUMHEAD_GROUP_SIZE; const int offset = head_num * head_dim * 4; const int offset_head = y * head_dim * 4; __global const FLOAT *A_offset = input0 + x * offset + offset_head; - __global FLOAT *Pastkey_offset = past_key + z * offset + offset_head; + __global FLOAT *Pastkey_offset = past_key + (z * kv_head_num + yin) * head_dim * 4; const int z4 = z << 2; - COMPUTE_FLOAT4 Vscale = (COMPUTE_FLOAT4)scale; + float4 Vscale = (float4)scale; #ifdef OPENCL_PREFILL_ATTENTION - __global const FLOAT *B_offset = input1 + z * offset + offset_head; + __global const FLOAT *B_offset = input1 + (z * kv_head_num + yin) * head_dim * 4; const int x4 = x << 2; const int query_seq_len4 = (query_seq_len + 3) / 4; const int output_offset = y * query_seq_len4 * key_seq_len * 4; - COMPUTE_FLOAT4 out0 = 0; - COMPUTE_FLOAT4 out1 = 0; - COMPUTE_FLOAT4 out2 = 0; - COMPUTE_FLOAT4 out3 = 0; + float4 out0 = 0; + float4 out1 = 0; + float4 out2 = 0; + float4 out3 = 0; const int head_dim4 = (head_dim + 3) / 4; #ifdef HEADDIM_LEAVE for(int i = 0; i < head_dim4 - 1; ++i){ - COMPUTE_FLOAT16 A = CONVERT_COMPUTE_FLOAT16(vload16(i, A_offset)); - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(i, B_offset)); + float16 A = convert_float16(vload16(i, A_offset)); + float16 B = convert_float16(vload16(i, B_offset)); - out0 = mad(A.s0123, (COMPUTE_FLOAT4)B.s0, out0); - out1 = mad(A.s0123, (COMPUTE_FLOAT4)B.s1, out1); - out2 = mad(A.s0123, (COMPUTE_FLOAT4)B.s2, out2); - out3 = mad(A.s0123, (COMPUTE_FLOAT4)B.s3, out3); + out0 = mad(A.s0123, (float4)B.s0, out0); + out1 = mad(A.s0123, (float4)B.s1, out1); + out2 = mad(A.s0123, (float4)B.s2, out2); + out3 = mad(A.s0123, (float4)B.s3, out3); - out0 = mad(A.s4567, (COMPUTE_FLOAT4)B.s4, out0); - out1 = mad(A.s4567, (COMPUTE_FLOAT4)B.s5, out1); - out2 = mad(A.s4567, (COMPUTE_FLOAT4)B.s6, out2); - out3 = mad(A.s4567, (COMPUTE_FLOAT4)B.s7, out3); + out0 = mad(A.s4567, (float4)B.s4, out0); + out1 = mad(A.s4567, (float4)B.s5, out1); + out2 = mad(A.s4567, (float4)B.s6, out2); + out3 = mad(A.s4567, (float4)B.s7, out3); - out0 = mad(A.s89ab, (COMPUTE_FLOAT4)B.s8, out0); - out1 = mad(A.s89ab, (COMPUTE_FLOAT4)B.s9, out1); - out2 = mad(A.s89ab, (COMPUTE_FLOAT4)B.sa, out2); - out3 = mad(A.s89ab, (COMPUTE_FLOAT4)B.sb, out3); + out0 = mad(A.s89ab, (float4)B.s8, out0); + out1 = mad(A.s89ab, (float4)B.s9, out1); + out2 = mad(A.s89ab, (float4)B.sa, out2); + out3 = mad(A.s89ab, (float4)B.sb, out3); - out0 = mad(A.scdef, (COMPUTE_FLOAT4)B.sc, out0); - out1 = mad(A.scdef, (COMPUTE_FLOAT4)B.sd, out1); - out2 = mad(A.scdef, (COMPUTE_FLOAT4)B.se, out2); - out3 = mad(A.scdef, (COMPUTE_FLOAT4)B.sf, out3); + out0 = mad(A.scdef, (float4)B.sc, out0); + out1 = mad(A.scdef, (float4)B.sd, out1); + out2 = mad(A.scdef, (float4)B.se, out2); + out3 = mad(A.scdef, (float4)B.sf, out3); vstore16(CONVERT_FLOAT16(B), i, Pastkey_offset); } for(int i = (head_dim4 - 1) * 4; i < head_dim; ++i){ - COMPUTE_FLOAT4 A = CONVERT_COMPUTE_FLOAT4(vload4(i, A_offset)); - COMPUTE_FLOAT4 B = CONVERT_COMPUTE_FLOAT4(vload4(i, B_offset)); + float4 A = convert_float4(vload4(i, A_offset)); + float4 B = convert_float4(vload4(i, B_offset)); - out0 = mad(A, (COMPUTE_FLOAT4)B.s0, out0); - out1 = mad(A, (COMPUTE_FLOAT4)B.s1, out1); - out2 = mad(A, (COMPUTE_FLOAT4)B.s2, out2); - out3 = mad(A, (COMPUTE_FLOAT4)B.s3, out3); + out0 = mad(A, (float4)B.s0, out0); + out1 = mad(A, (float4)B.s1, out1); + out2 = mad(A, (float4)B.s2, out2); + out3 = mad(A, (float4)B.s3, out3); vstore4(CONVERT_FLOAT4(B), i, Pastkey_offset); } #else for(int i = 0; i < head_dim4; ++i){ - COMPUTE_FLOAT16 A = CONVERT_COMPUTE_FLOAT16(vload16(i, A_offset)); - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(i, B_offset)); + float16 A = convert_float16(vload16(i, A_offset)); + float16 B = convert_float16(vload16(i, B_offset)); - out0 = mad(A.s0123, (COMPUTE_FLOAT4)B.s0, out0); - out1 = mad(A.s0123, (COMPUTE_FLOAT4)B.s1, out1); - out2 = mad(A.s0123, (COMPUTE_FLOAT4)B.s2, out2); - out3 = mad(A.s0123, (COMPUTE_FLOAT4)B.s3, out3); + out0 = mad(A.s0123, (float4)B.s0, out0); + out1 = mad(A.s0123, (float4)B.s1, out1); + out2 = mad(A.s0123, (float4)B.s2, out2); + out3 = mad(A.s0123, (float4)B.s3, out3); - out0 = mad(A.s4567, (COMPUTE_FLOAT4)B.s4, out0); - out1 = mad(A.s4567, (COMPUTE_FLOAT4)B.s5, out1); - out2 = mad(A.s4567, (COMPUTE_FLOAT4)B.s6, out2); - out3 = mad(A.s4567, (COMPUTE_FLOAT4)B.s7, out3); + out0 = mad(A.s4567, (float4)B.s4, out0); + out1 = mad(A.s4567, (float4)B.s5, out1); + out2 = mad(A.s4567, (float4)B.s6, out2); + out3 = mad(A.s4567, (float4)B.s7, out3); - out0 = mad(A.s89ab, (COMPUTE_FLOAT4)B.s8, out0); - out1 = mad(A.s89ab, (COMPUTE_FLOAT4)B.s9, out1); - out2 = mad(A.s89ab, (COMPUTE_FLOAT4)B.sa, out2); - out3 = mad(A.s89ab, (COMPUTE_FLOAT4)B.sb, out3); + out0 = mad(A.s89ab, (float4)B.s8, out0); + out1 = mad(A.s89ab, (float4)B.s9, out1); + out2 = mad(A.s89ab, (float4)B.sa, out2); + out3 = mad(A.s89ab, (float4)B.sb, out3); - out0 = mad(A.scdef, (COMPUTE_FLOAT4)B.sc, out0); - out1 = mad(A.scdef, (COMPUTE_FLOAT4)B.sd, out1); - out2 = mad(A.scdef, (COMPUTE_FLOAT4)B.se, out2); - out3 = mad(A.scdef, (COMPUTE_FLOAT4)B.sf, out3); + out0 = mad(A.scdef, (float4)B.sc, out0); + out1 = mad(A.scdef, (float4)B.sd, out1); + out2 = mad(A.scdef, (float4)B.se, out2); + out3 = mad(A.scdef, (float4)B.sf, out3); vstore16(CONVERT_FLOAT16(B), i, Pastkey_offset); } @@ -121,46 +123,22 @@ __kernel void matmul_qk_div_mask(GLOBAL_SIZE_3_DIMS out2 *= Vscale; out3 *= Vscale; + float4 mask0, mask1, mask2, mask3; + mask = mask + (x4 * key_seq_len + z4) * 4; + mask0.s0 = mask[0]; mask1.s0 = mask[4]; mask2.s0 = mask[8]; mask3.s0 = mask[12]; mask += key_seq_len * 4; + mask0.s1 = mask[0]; mask1.s1 = mask[4]; mask2.s1 = mask[8]; mask3.s1 = mask[12]; mask += key_seq_len * 4; + mask0.s2 = mask[0]; mask1.s2 = mask[4]; mask2.s2 = mask[8]; mask3.s2 = mask[12]; mask += key_seq_len * 4; + mask0.s3 = mask[0]; mask1.s3 = mask[4]; mask2.s3 = mask[8]; mask3.s3 = mask[12]; #ifdef ADD_MASK - out0.s0 += mask[((x4 + 0) * key_seq_len + (z4 + 0)) * 4]; - out1.s0 += mask[((x4 + 0) * key_seq_len + (z4 + 1)) * 4]; - out2.s0 += mask[((x4 + 0) * key_seq_len + (z4 + 2)) * 4]; - out3.s0 += mask[((x4 + 0) * key_seq_len + (z4 + 3)) * 4]; - - out0.s1 += mask[((x4 + 1) * key_seq_len + (z4 + 0)) * 4]; - out1.s1 += mask[((x4 + 1) * key_seq_len + (z4 + 1)) * 4]; - out2.s1 += mask[((x4 + 1) * key_seq_len + (z4 + 2)) * 4]; - out3.s1 += mask[((x4 + 1) * key_seq_len + (z4 + 3)) * 4]; - - out0.s2 += mask[((x4 + 2) * key_seq_len + (z4 + 0)) * 4]; - out1.s2 += mask[((x4 + 2) * key_seq_len + (z4 + 1)) * 4]; - out2.s2 += mask[((x4 + 2) * key_seq_len + (z4 + 2)) * 4]; - out3.s2 += mask[((x4 + 2) * key_seq_len + (z4 + 3)) * 4]; - - out0.s3 += mask[((x4 + 3) * key_seq_len + (z4 + 0)) * 4]; - out1.s3 += mask[((x4 + 3) * key_seq_len + (z4 + 1)) * 4]; - out2.s3 += mask[((x4 + 3) * key_seq_len + (z4 + 2)) * 4]; - out3.s3 += mask[((x4 + 3) * key_seq_len + (z4 + 3)) * 4]; + out0 += mask0; + out1 += mask1; + out2 += mask2; + out3 += mask3; #else - out0.s0 = mask[((x4 + 0) * key_seq_len + (z4 + 0)) * 4] == 0 ? -FLT_MAX : out0.s0; - out1.s0 = mask[((x4 + 0) * key_seq_len + (z4 + 1)) * 4] == 0 ? -FLT_MAX : out1.s0; - out2.s0 = mask[((x4 + 0) * key_seq_len + (z4 + 2)) * 4] == 0 ? -FLT_MAX : out2.s0; - out3.s0 = mask[((x4 + 0) * key_seq_len + (z4 + 3)) * 4] == 0 ? -FLT_MAX : out3.s0; - - out0.s1 = mask[((x4 + 1) * key_seq_len + (z4 + 0)) * 4] == 0 ? -FLT_MAX : out0.s1; - out1.s1 = mask[((x4 + 1) * key_seq_len + (z4 + 1)) * 4] == 0 ? -FLT_MAX : out1.s1; - out2.s1 = mask[((x4 + 1) * key_seq_len + (z4 + 2)) * 4] == 0 ? -FLT_MAX : out2.s1; - out3.s1 = mask[((x4 + 1) * key_seq_len + (z4 + 3)) * 4] == 0 ? -FLT_MAX : out3.s1; - - out0.s2 = mask[((x4 + 2) * key_seq_len + (z4 + 0)) * 4] == 0 ? -FLT_MAX : out0.s2; - out1.s2 = mask[((x4 + 2) * key_seq_len + (z4 + 1)) * 4] == 0 ? -FLT_MAX : out1.s2; - out2.s2 = mask[((x4 + 2) * key_seq_len + (z4 + 2)) * 4] == 0 ? -FLT_MAX : out2.s2; - out3.s2 = mask[((x4 + 2) * key_seq_len + (z4 + 3)) * 4] == 0 ? -FLT_MAX : out3.s2; - - out0.s3 = mask[((x4 + 3) * key_seq_len + (z4 + 0)) * 4] == 0 ? -FLT_MAX : out0.s3; - out1.s3 = mask[((x4 + 3) * key_seq_len + (z4 + 1)) * 4] == 0 ? -FLT_MAX : out1.s3; - out2.s3 = mask[((x4 + 3) * key_seq_len + (z4 + 2)) * 4] == 0 ? -FLT_MAX : out2.s3; - out3.s3 = mask[((x4 + 3) * key_seq_len + (z4 + 3)) * 4] == 0 ? -FLT_MAX : out3.s3; + out0 = (mask0 == (float4)0) ? (float4)(-FLT_MAX) : out0; + out1 = (mask1 == (float4)0) ? (float4)(-FLT_MAX) : out1; + out2 = (mask2 == (float4)0) ? (float4)(-FLT_MAX) : out2; + out3 = (mask3 == (float4)0) ? (float4)(-FLT_MAX) : out3; #endif vstore4(CONVERT_FLOAT4(out0), 0, output + output_offset + x * key_seq_len * 4 + z4 * 4); @@ -171,49 +149,49 @@ __kernel void matmul_qk_div_mask(GLOBAL_SIZE_3_DIMS if(z4 + 3 >= key_seq_len) return; vstore4(CONVERT_FLOAT4(out3), 0, output + output_offset + x * key_seq_len * 4 + (z4 + 3) * 4); #else - __global const FLOAT *B_offset = input1 + offset_head; + __global const FLOAT *B_offset = input1 + yin * head_dim * 4; const int key_seq_len4 = (key_seq_len + 3) / 4; - COMPUTE_FLOAT4 out = 0; + float4 out = 0; const int head_dim4 = (head_dim + 3) / 4; #ifdef HEADDIM_LEAVE for(int i = 0; i < head_dim4 - 1; ++i){ - COMPUTE_FLOAT16 A = CONVERT_COMPUTE_FLOAT16(vload16(i, A_offset)); - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(i, Pastkey_offset)); + float16 A = convert_float16(vload16(i, A_offset)); + float16 B = convert_float16(vload16(i, Pastkey_offset)); - out = mad((COMPUTE_FLOAT4)A.s0, B.s0123, out); - out = mad((COMPUTE_FLOAT4)A.s4, B.s4567, out); - out = mad((COMPUTE_FLOAT4)A.s8, B.s89ab, out); - out = mad((COMPUTE_FLOAT4)A.sc, B.scdef, out); + out = mad((float4)A.s0, B.s0123, out); + out = mad((float4)A.s4, B.s4567, out); + out = mad((float4)A.s8, B.s89ab, out); + out = mad((float4)A.sc, B.scdef, out); } for(int i = (head_dim4 - 1) * 4; i < head_dim; ++i){ - COMPUTE_FLOAT4 A = CONVERT_COMPUTE_FLOAT4(vload4(i, A_offset)); - COMPUTE_FLOAT4 B = CONVERT_COMPUTE_FLOAT4(vload4(i, Pastkey_offset)); + float4 A = convert_float4(vload4(i, A_offset)); + float4 B = convert_float4(vload4(i, Pastkey_offset)); - out = mad((COMPUTE_FLOAT4)A.s0, B, out); + out = mad((float4)A.s0, B, out); } #else for(int i = 0; i < head_dim4; ++i){ - COMPUTE_FLOAT16 A = CONVERT_COMPUTE_FLOAT16(vload16(i, A_offset)); - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(i, Pastkey_offset)); + float16 A = convert_float16(vload16(i, A_offset)); + float16 B = convert_float16(vload16(i, Pastkey_offset)); - out = mad((COMPUTE_FLOAT4)A.s0, B.s0123, out); - out = mad((COMPUTE_FLOAT4)A.s4, B.s4567, out); - out = mad((COMPUTE_FLOAT4)A.s8, B.s89ab, out); - out = mad((COMPUTE_FLOAT4)A.sc, B.scdef, out); + out = mad((float4)A.s0, B.s0123, out); + out = mad((float4)A.s4, B.s4567, out); + out = mad((float4)A.s8, B.s89ab, out); + out = mad((float4)A.sc, B.scdef, out); } #endif if(z == key_seq_len4 - 1){ int remain = key_seq_len - z * 4 - 1; Pastkey_offset += remain; - COMPUTE_FLOAT tmp = 0; + float tmp = 0; for(int i = 0; i < head_dim; ++i){ - COMPUTE_FLOAT A = A_offset[i*4]; - COMPUTE_FLOAT B = B_offset[i*4]; + float A = A_offset[i*4]; + float B = B_offset[i*4]; Pastkey_offset[i * 4] = B; tmp += A * B; } - COMPUTE_FLOAT *out_ptr = (COMPUTE_FLOAT*)&out; + float *out_ptr = (float*)&out; out_ptr[remain] = tmp; } out *= Vscale; @@ -229,6 +207,7 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS __private const int qk_seq_len, __private const int value_seq_len, __private const int head_num, + __private const int kv_head_num, __private const int head_dim) { const int x = get_global_id(0); // prefill qk_seq_len / 4 decode 1 @@ -237,14 +216,16 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS const int z4 = z << 2; DEAL_NON_UNIFORM_DIM3(x, y, z); + const int yin = y / NUMHEAD_GROUP_SIZE; #ifdef OPENCL_PREFILL_ATTENTION const int offset = head_num * head_dim * 4; + const int stride = kv_head_num * head_dim * 4; const int offset_head = y * head_dim * 4 + z4 * 4; const int value_seq_len4 = (value_seq_len + 3) / 4; const int qk_seq_len4 = (qk_seq_len + 3) / 4; __global const FLOAT *A_offset = input0 + (y * qk_seq_len4 + x) * value_seq_len * 4; - __global const FLOAT *B_offset = input1 + offset_head; - __global FLOAT *Pastvalue_offset = past_value + offset_head; + __global const FLOAT *B_offset = input1 + yin * head_dim * 4 + z4 * 4; + __global FLOAT *Pastvalue_offset = past_value + yin * head_dim * 4 + z4 * 4; COMPUTE_FLOAT4 out0 = 0; COMPUTE_FLOAT4 out1 = 0; COMPUTE_FLOAT4 out2 = 0; @@ -256,7 +237,7 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS COMPUTE_FLOAT4 A1 = CONVERT_COMPUTE_FLOAT4(vload4(index + 1, A_offset)); COMPUTE_FLOAT4 A2 = CONVERT_COMPUTE_FLOAT4(vload4(index + 2, A_offset)); COMPUTE_FLOAT4 A3 = CONVERT_COMPUTE_FLOAT4(vload4(index + 3, A_offset)); - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, B_offset + i * offset)); + COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, B_offset + i * stride)); out0 = mad(A0, (COMPUTE_FLOAT4)B.s0, out0); out0 = mad(A1, (COMPUTE_FLOAT4)B.s1, out0); @@ -278,11 +259,11 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS out3 = mad(A2, (COMPUTE_FLOAT4)B.se, out3); out3 = mad(A3, (COMPUTE_FLOAT4)B.sf, out3); - vstore16(CONVERT_FLOAT16(B), 0, Pastvalue_offset + i * offset); + vstore16(CONVERT_FLOAT16(B), 0, Pastvalue_offset + i * stride); } #ifdef HEADDIM_LEAVE - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, B_offset + (value_seq_len4 - 1) * offset)); + COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, B_offset + (value_seq_len4 - 1) * stride)); COMPUTE_FLOAT *B_ptr = (COMPUTE_FLOAT*)&B; for(int i = (value_seq_len4 - 1) * 4, j = 0; i < value_seq_len; ++i, ++j){ COMPUTE_FLOAT4 A0 = CONVERT_COMPUTE_FLOAT4(vload4(i, A_offset)); @@ -292,19 +273,19 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS out3 = mad(A0, (COMPUTE_FLOAT4)B_ptr[j + 12], out3); } vstore4(CONVERT_FLOAT4(out0), 0, output + x * offset + (y * head_dim + z4) * 4); - vstore4(CONVERT_FLOAT4(B.s0123), 0, Pastvalue_offset + (value_seq_len4 - 1) * offset); + vstore4(CONVERT_FLOAT4(B.s0123), 0, Pastvalue_offset + (value_seq_len4 - 1) * stride); if(z4 + 1 >= head_dim) return; vstore4(CONVERT_FLOAT4(out1), 0, output + x * offset + (y * head_dim + z4 + 1) * 4); - vstore4(CONVERT_FLOAT4(B.s4567), 1, Pastvalue_offset + (value_seq_len4 - 1) * offset); + vstore4(CONVERT_FLOAT4(B.s4567), 1, Pastvalue_offset + (value_seq_len4 - 1) * stride); if(z4 + 2 >= head_dim) return; vstore4(CONVERT_FLOAT4(out2), 0, output + x * offset + (y * head_dim + z4 + 2) * 4); - vstore4(CONVERT_FLOAT4(B.s89ab), 2, Pastvalue_offset + (value_seq_len4 - 1) * offset); + vstore4(CONVERT_FLOAT4(B.s89ab), 2, Pastvalue_offset + (value_seq_len4 - 1) * stride); if(z4 + 3 >= head_dim) return; vstore4(CONVERT_FLOAT4(out3), 0, output + x * offset + (y * head_dim + z4 + 3) * 4); - vstore4(CONVERT_FLOAT4(B.scdef), 3, Pastvalue_offset + (value_seq_len4 - 1) * offset); + vstore4(CONVERT_FLOAT4(B.scdef), 3, Pastvalue_offset + (value_seq_len4 - 1) * stride); #else - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, B_offset + (value_seq_len4 - 1) * offset)); - vstore16(CONVERT_FLOAT16(B), 0, Pastvalue_offset + (value_seq_len4 - 1) * offset); + COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, B_offset + (value_seq_len4 - 1) * stride)); + vstore16(CONVERT_FLOAT16(B), 0, Pastvalue_offset + (value_seq_len4 - 1) * stride); COMPUTE_FLOAT *B_ptr = (COMPUTE_FLOAT*)&B; for(int i = (value_seq_len4 - 1) * 4, j = 0; i < value_seq_len; ++i, ++j){ COMPUTE_FLOAT4 A0 = CONVERT_COMPUTE_FLOAT4(vload4(i, A_offset)); @@ -318,17 +299,18 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS #else const int value_seq_len4 = (value_seq_len + 3) / 4; + const int stride = kv_head_num * head_dim * 4; const int offset = head_num * head_dim * 4; const int offset_head = y * head_dim * 4 + z4 * 4; const int loop = (value_seq_len + 2) / 4; __global const FLOAT *A_offset = input0 + y * value_seq_len4 * 4; - __global const FLOAT *B_offset = input1 + offset_head; - __global FLOAT *Pastvalue_offset = past_value + offset_head; + __global const FLOAT *B_offset = input1 + yin * head_dim * 4 + z4 * 4; + __global FLOAT *Pastvalue_offset = past_value + yin * head_dim * 4 + z4 * 4; COMPUTE_FLOAT4 out = 0; for(int i = 0; i < loop - 1; i++){ COMPUTE_FLOAT4 A = CONVERT_COMPUTE_FLOAT4(vload4(i, A_offset)); - COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, Pastvalue_offset + i * offset)); + COMPUTE_FLOAT16 B = CONVERT_COMPUTE_FLOAT16(vload16(0, Pastvalue_offset + i * stride)); out.s0 += dot(A, B.s0123); out.s1 += dot(A, B.s4567); @@ -336,7 +318,7 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS out.s3 += dot(A, B.scdef); } int start = (loop - 1) < 0 ? 0 : (loop - 1); - COMPUTE_FLOAT16 B_Vec = CONVERT_COMPUTE_FLOAT16(vload16(0, Pastvalue_offset + start * offset)); + COMPUTE_FLOAT16 B_Vec = CONVERT_COMPUTE_FLOAT16(vload16(0, Pastvalue_offset + start * stride)); COMPUTE_FLOAT *B_ptr = (COMPUTE_FLOAT *)&B_Vec; for(int i = start * 4; i < value_seq_len - 1; ++i){ COMPUTE_FLOAT A = A_offset[i]; @@ -356,7 +338,7 @@ __kernel void matmul_qkv(GLOBAL_SIZE_3_DIMS out.s1 += A * B1; out.s2 += A * B2; out.s3 += A * B3; - int index = ((value_seq_len - 1) >> 2) * offset + ((value_seq_len - 1) % 4); + int index = ((value_seq_len - 1) >> 2) * stride + ((value_seq_len - 1) % 4); #ifdef HEADDIM_LEAVE Pastvalue_offset[index] = B0; diff --git a/source/backend/opencl/execution/cl/buffer_convert_buf.cl b/source/backend/opencl/execution/cl/buffer_convert_buf.cl index 0177d3d41..1563c65ea 100644 --- a/source/backend/opencl/execution/cl/buffer_convert_buf.cl +++ b/source/backend/opencl/execution/cl/buffer_convert_buf.cl @@ -290,127 +290,6 @@ __kernel void conv2d_filter_buffer_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS vstore4(output_values, 0, output+out_offset); } -#ifdef USE_LOW_BIT_WEIGHT_INT8 -// convert kernel : from int8 buffer(oihw) to int8 image(oc/4 h w , ic oc4) -__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int8(GLOBAL_SIZE_2_DIMS - __global const char *input_ptr, - __private const int output_channel, - __private const int2 kernel_shape, - __private const int ic_h_w_size, - __private const int height_width_size, - __global char *output) { - int image_width_idx = get_global_id(0); // ic - int image_height_idx = get_global_id(1); // oc/4 h w - - DEAL_NON_UNIFORM_DIM2(image_width_idx, image_height_idx); - - const int input_channel_4_idx = image_width_idx; - const int output_channel_4_idx = (image_height_idx / height_width_size) * 4; - const int height_width_idx = image_height_idx % height_width_size; - const int buffer_height_idx = height_width_idx / kernel_shape.y; - const int buffer_width_idx = height_width_idx % kernel_shape.y; - - const int buffer_offset = output_channel_4_idx * ic_h_w_size + input_channel_4_idx * height_width_size + - buffer_height_idx * kernel_shape.y + buffer_width_idx; - - char4 output_values = 0; - if (output_channel_4_idx < output_channel) { - const int remain_channel = output_channel - output_channel_4_idx; - if (remain_channel >= 4) { - int offset = buffer_offset; - output_values.x = (char)(*(input_ptr + offset)); - offset = mad24(1, ic_h_w_size, offset); - output_values.y = (char)(*(input_ptr + offset)); - offset += ic_h_w_size; - output_values.z = (char)(*(input_ptr + offset)); - offset += ic_h_w_size; - output_values.w = (char)(*(input_ptr + offset)); - } else if (remain_channel == 3) { - int offset = buffer_offset; - output_values.x = (char)(*(input_ptr + offset)); - offset = mad24(1, ic_h_w_size, offset); - output_values.y = (char)(*(input_ptr + offset)); - offset += ic_h_w_size; - output_values.z = (char)(*(input_ptr + offset)); - - } else if (remain_channel == 2) { - int offset = buffer_offset; - output_values.x = (char)(*(input_ptr + offset)); - offset = mad24(1, ic_h_w_size, offset); - output_values.y = (char)(*(input_ptr + offset)); - } else if (remain_channel == 1) { - int offset = buffer_offset; - output_values.x = (char)(*(input_ptr + offset)); - } - } - const int out_offset = (image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*4; - vstore4(output_values, 0, output+out_offset); -} -#endif - -#ifdef USE_LOW_BIT_WEIGHT_INT4 -// convert kernel : from int8 buffer(oihw) to int4 image(oc/4 h w , ic oc4) -__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int4(GLOBAL_SIZE_2_DIMS - __global const char *input_ptr, - __private const int output_channel, - __private const int2 kernel_shape, - __private const int ic_h_w_size, - __private const int height_width_size, - __global uchar *output) { - int image_width_idx = get_global_id(0); // ic - int image_height_idx = get_global_id(1); // oc/4 h w - - DEAL_NON_UNIFORM_DIM2(image_width_idx, image_height_idx); - - const int input_channel_4_idx = image_width_idx; - const int output_channel_4_idx = (image_height_idx / height_width_size) * 4; - const int height_width_idx = image_height_idx % height_width_size; - const int buffer_height_idx = height_width_idx / kernel_shape.y; - const int buffer_width_idx = height_width_idx % kernel_shape.y; - - const int buffer_offset = output_channel_4_idx * ic_h_w_size + input_channel_4_idx * height_width_size + - buffer_height_idx * kernel_shape.y + buffer_width_idx; - - char4 output_values_int8 = 0; - if (output_channel_4_idx < output_channel) { - const int remain_channel = output_channel - output_channel_4_idx; - if (remain_channel >= 4) { - int offset = buffer_offset; - output_values_int8.x = (char)(*(input_ptr + offset)); - offset = mad24(1, ic_h_w_size, offset); - output_values_int8.y = (char)(*(input_ptr + offset)); - offset += ic_h_w_size; - output_values_int8.z = (char)(*(input_ptr + offset)); - offset += ic_h_w_size; - output_values_int8.w = (char)(*(input_ptr + offset)); - } else if (remain_channel == 3) { - int offset = buffer_offset; - output_values_int8.x = (char)(*(input_ptr + offset)); - offset = mad24(1, ic_h_w_size, offset); - output_values_int8.y = (char)(*(input_ptr + offset)); - offset += ic_h_w_size; - output_values_int8.z = (char)(*(input_ptr + offset)); - - } else if (remain_channel == 2) { - int offset = buffer_offset; - output_values_int8.x = (char)(*(input_ptr + offset)); - offset = mad24(1, ic_h_w_size, offset); - output_values_int8.y = (char)(*(input_ptr + offset)); - } else if (remain_channel == 1) { - int offset = buffer_offset; - output_values_int8.x = (char)(*(input_ptr + offset)); - } - } - - uchar2 output_values_int4 = (uchar2)(0, 0); - output_values_int4.s0 = (output_values_int8.x + 8) * 16 + (output_values_int8.y + 8); - output_values_int4.s1 = (output_values_int8.z + 8) * 16 + (output_values_int8.w + 8); - - const int out_offset = (image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*2; - vstore2(output_values_int4, 0, output+out_offset); -} -#endif - // convert kernel : from buffer(oihw) to image(oc/4 h w , ic oc4) __kernel void conv2d_filter_buffer_to_nc4hw4_buffer_floatin(GLOBAL_SIZE_2_DIMS __global const float *input_ptr, diff --git a/source/backend/opencl/execution/cl/buffer_convert_quant.cl b/source/backend/opencl/execution/cl/buffer_convert_quant.cl new file mode 100644 index 000000000..1215cc71b --- /dev/null +++ b/source/backend/opencl/execution/cl/buffer_convert_quant.cl @@ -0,0 +1,242 @@ +#ifdef MNN_SUPPORT_FP16 +#pragma OPENCL EXTENSION cl_khr_fp16 : enable +#endif + +__constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST; +#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0, __private const int global_size_dim1, +#define DEAL_NON_UNIFORM_DIM2(input1, input2) \ + if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { \ + return; \ + } + +#ifdef USE_LOW_BIT_WEIGHT_INT8 +// convert kernel : from int8 buffer(oihw) to int8 image(oc/4 h w , ic oc4) +__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int8(GLOBAL_SIZE_2_DIMS + __global const char *input_ptr, + __private const int output_channel, + __private const int2 kernel_shape, + __private const int ic_h_w_size, + __private const int height_width_size, + __global char *output) { + int image_width_idx = get_global_id(0); // ic + int image_height_idx = get_global_id(1); // oc/4 h w + + DEAL_NON_UNIFORM_DIM2(image_width_idx, image_height_idx); + + const int input_channel_4_idx = image_width_idx; + const int output_channel_4_idx = (image_height_idx / height_width_size) * 4; + const int height_width_idx = image_height_idx % height_width_size; + const int buffer_height_idx = height_width_idx / kernel_shape.y; + const int buffer_width_idx = height_width_idx % kernel_shape.y; + + const int buffer_offset = output_channel_4_idx * ic_h_w_size + input_channel_4_idx * height_width_size + + buffer_height_idx * kernel_shape.y + buffer_width_idx; + + char4 output_values = 0; + if (output_channel_4_idx < output_channel) { + const int remain_channel = output_channel - output_channel_4_idx; + if (remain_channel >= 4) { + int offset = buffer_offset; + output_values.x = (char)(*(input_ptr + offset)); + offset = mad24(1, ic_h_w_size, offset); + output_values.y = (char)(*(input_ptr + offset)); + offset += ic_h_w_size; + output_values.z = (char)(*(input_ptr + offset)); + offset += ic_h_w_size; + output_values.w = (char)(*(input_ptr + offset)); + } else if (remain_channel == 3) { + int offset = buffer_offset; + output_values.x = (char)(*(input_ptr + offset)); + offset = mad24(1, ic_h_w_size, offset); + output_values.y = (char)(*(input_ptr + offset)); + offset += ic_h_w_size; + output_values.z = (char)(*(input_ptr + offset)); + + } else if (remain_channel == 2) { + int offset = buffer_offset; + output_values.x = (char)(*(input_ptr + offset)); + offset = mad24(1, ic_h_w_size, offset); + output_values.y = (char)(*(input_ptr + offset)); + } else if (remain_channel == 1) { + int offset = buffer_offset; + output_values.x = (char)(*(input_ptr + offset)); + } + } + const int out_offset = (image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*4; + vstore4(output_values, 0, output+out_offset); +} +#endif + +#ifdef USE_LOW_BIT_WEIGHT_INT4 +// convert kernel : from int8 buffer(oihw) to int4 image(oc/4 h w , ic oc4) +__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int4(GLOBAL_SIZE_2_DIMS + __global const char *input_ptr, + __private const int output_channel, + __private const int2 kernel_shape, + __private const int ic_h_w_size, + __private const int height_width_size, + __global uchar *output) { + int image_width_idx = get_global_id(0); // ic + int image_height_idx = get_global_id(1); // oc/4 h w + + DEAL_NON_UNIFORM_DIM2(image_width_idx, image_height_idx); + + const int input_channel_4_idx = image_width_idx; + const int output_channel_4_idx = (image_height_idx / height_width_size) * 4; + const int height_width_idx = image_height_idx % height_width_size; + const int buffer_height_idx = height_width_idx / kernel_shape.y; + const int buffer_width_idx = height_width_idx % kernel_shape.y; + + const int buffer_offset = output_channel_4_idx * ic_h_w_size + input_channel_4_idx * height_width_size + + buffer_height_idx * kernel_shape.y + buffer_width_idx; + + char4 output_values_int8 = 0; + if (output_channel_4_idx < output_channel) { + const int remain_channel = output_channel - output_channel_4_idx; + if (remain_channel >= 4) { + int offset = buffer_offset; + output_values_int8.x = (char)(*(input_ptr + offset)); + offset = mad24(1, ic_h_w_size, offset); + output_values_int8.y = (char)(*(input_ptr + offset)); + offset += ic_h_w_size; + output_values_int8.z = (char)(*(input_ptr + offset)); + offset += ic_h_w_size; + output_values_int8.w = (char)(*(input_ptr + offset)); + } else if (remain_channel == 3) { + int offset = buffer_offset; + output_values_int8.x = (char)(*(input_ptr + offset)); + offset = mad24(1, ic_h_w_size, offset); + output_values_int8.y = (char)(*(input_ptr + offset)); + offset += ic_h_w_size; + output_values_int8.z = (char)(*(input_ptr + offset)); + + } else if (remain_channel == 2) { + int offset = buffer_offset; + output_values_int8.x = (char)(*(input_ptr + offset)); + offset = mad24(1, ic_h_w_size, offset); + output_values_int8.y = (char)(*(input_ptr + offset)); + } else if (remain_channel == 1) { + int offset = buffer_offset; + output_values_int8.x = (char)(*(input_ptr + offset)); + } + } + + uchar2 output_values_int4 = (uchar2)(0, 0); + output_values_int4.s0 = (output_values_int8.x + 8) * 16 + (output_values_int8.y + 8); + output_values_int4.s1 = (output_values_int8.z + 8) * 16 + (output_values_int8.w + 8); + + const int out_offset = (image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*2; + vstore2(output_values_int4, 0, output+out_offset); +} +#endif + +#define CHAR16_TO_UCHAR8(a, b) \ + a = (uchar8)(((b.s0 + 8) << 4) + b.s1 + 8, ((b.s2 + 8) << 4) + b.s3 + 8, ((b.s4 + 8) << 4) + b.s5 + 8, ((b.s6 + 8) << 4) + b.s7 + 8, ((b.s8 + 8) << 4) + b.s9 + 8, ((b.sa + 8) << 4) + b.sb + 8, ((b.sc + 8) << 4) + b.sd + 8, ((b.se + 8) << 4) + b.sf + 8); + +#define CHAR32_TO_UCHAR16(a, b, c) \ + a = (uchar16)(((b.s0 + 8) << 4) + b.s1 + 8, ((b.s2 + 8) << 4) + b.s3 + 8, ((b.s4 + 8) << 4) + b.s5 + 8, ((b.s6 + 8) << 4) + b.s7 + 8, ((b.s8 + 8) << 4) + b.s9 + 8, ((b.sa + 8) << 4) + b.sb + 8, ((b.sc + 8) << 4) + b.sd + 8, ((b.se + 8) << 4) + b.sf + 8, \ + ((c.s0 + 8) << 4) + c.s1 + 8, ((c.s2 + 8) << 4) + c.s3 + 8, ((c.s4 + 8) << 4) + c.s5 + 8, ((c.s6 + 8) << 4) + c.s7 + 8, ((c.s8 + 8) << 4) + c.s9 + 8, ((c.sa + 8) << 4) + c.sb + 8, ((c.sc + 8) << 4) + c.sd + 8, ((c.se + 8) << 4) + c.sf + 8); +__kernel void conv2d_1x1_weight_quant_buffer(GLOBAL_SIZE_2_DIMS + __global const char *input_ptr, +#ifdef USE_LOW_BIT_WEIGHT_INT4 + __global uchar *output_ptr, +#else + __global char *output_ptr, +#endif + __private const int input_channel, + __private const int output_channel) { + int x = get_global_id(0); // ic / 16 + int y = get_global_id(1); // oc + + DEAL_NON_UNIFORM_DIM2(x, y); + const int xin = x << 4; + const int outputChannelC4 = (output_channel + 3) >> 2; + const int inputOffset = y * input_channel + xin; + char16 weight = 0; +#ifdef INPUT_CHANNEL_LEAVE + if(xin + 15 >= input_channel){ + char *weight_ptr = (char*)&weight; + for(int i = 0, j = 0; xin + i < input_channel && j < 16; ++i, ++j){ + weight_ptr[j] = input_ptr[inputOffset + i]; + } + }else { + weight = vload16(0, input_ptr + inputOffset); + } +#else + weight = vload16(0, input_ptr + inputOffset); +#endif + +#ifdef USE_LOW_BIT_WEIGHT_INT4 + const int outputOffset = ((x * outputChannelC4 * 4 * 8 + y * 8)); + uchar8 outWeight; + CHAR16_TO_UCHAR8(outWeight, weight); + vstore8(outWeight, 0, output_ptr + outputOffset); +#else + const int outputOffset = (x * outputChannelC4 * 4 + y) << 4; + vstore16(weight, 0, output_ptr + outputOffset); +#endif +} + +__kernel void conv2d_1x1_weight_quant_image(GLOBAL_SIZE_2_DIMS + __global const char *input_ptr, + __write_only image2d_t output, + __private const int input_channel, + __private const int output_channel) { + +#ifdef USE_LOW_BIT_WEIGHT_INT4 + int x = get_global_id(0); // ic / 32 + int y = get_global_id(1); // oc + + DEAL_NON_UNIFORM_DIM2(x, y); + const int outputChannelC4 = (output_channel + 3) >> 2; + const int xin = x << 5; + const int inputOffset = y * input_channel + xin; + char16 weight00 = 0, weight01 = 0; +#ifdef INPUT_CHANNEL_LEAVE + if(xin + 31 >= input_channel){ + char *weight00_ptr = (char*)&weight00; + char *weight01_ptr = (char*)&weight01; + int i = 0; + for(int j = 0; xin + i < input_channel && j < 16; ++i, ++j){ + weight00_ptr[j] = input_ptr[inputOffset + i]; + } + for(int j = 0; xin + i < input_channel && j < 16; ++i, ++j){ + weight01_ptr[j] = input_ptr[inputOffset + i]; + } + }else { + weight00 = vload16(0, input_ptr + inputOffset); + weight01 = vload16(0, input_ptr + inputOffset + 16); + } +#else + weight00 = vload16(0, input_ptr + inputOffset); + weight01 = vload16(0, input_ptr + inputOffset + 16); +#endif + + uchar16 outWeight; + CHAR32_TO_UCHAR16(outWeight, weight00, weight01); + write_imagei(output, (int2)(y, x), as_int4(outWeight)); +#else + int x = get_global_id(0); // ic / 16 + int y = get_global_id(1); // oc + + DEAL_NON_UNIFORM_DIM2(x, y); + const int xin = x << 4; + const int inputOffset = y * input_channel + xin; + const int outputChannelC4 = (output_channel + 3) >> 2; + char16 weight = 0; +#ifdef INPUT_CHANNEL_LEAVE + if(xin + 15 >= input_channel){ + char *weight_ptr = (char*)&weight; + for(int i = 0, j = 0; xin + i < input_channel && j < 16; ++i, ++j){ + weight_ptr[j] = input_ptr[inputOffset + i]; + } + }else { + weight = vload16(0, input_ptr + inputOffset); + } +#else + weight = vload16(0, input_ptr + inputOffset); +#endif + + write_imagei(output, (int2)(y, x), as_int4(weight)); +#endif +} diff --git a/source/backend/opencl/execution/cl/conv_2d.cl b/source/backend/opencl/execution/cl/conv_2d.cl index c3a807cb7..2b0bbad14 100644 --- a/source/backend/opencl/execution/cl/conv_2d.cl +++ b/source/backend/opencl/execution/cl/conv_2d.cl @@ -45,6 +45,16 @@ __constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | #define UNIT 4 #define MOD_NUM 15 +#ifdef INPUT_CHANNEL_LEAVE + #define PADZEROSVEC(k, channel, data0, data1, data2, data3) \ + data0 = (k << 2) < channel ? data0 : 0; \ + data1 = (k << 2) + 1 < channel ? data1 : 0; \ + data2 = (k << 2) + 2 < channel ? data2 : 0; \ + data3 = (k << 2) + 3 < channel ? data3 : 0; +#else + #define PADZEROSVEC(k, channel, data0, data1, data2, data3) +#endif + __kernel #if SET_ATTRIBUTE __attribute__((work_group_size_hint(16, 16, 1))) @@ -184,12 +194,10 @@ __attribute__((work_group_size_hint(16, 16, 1))) void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_BUFFER) __global const FLOAT *weights, #else @@ -201,7 +209,12 @@ void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, __private const int in_channel_block, __private const int2 output_shape, __private const int2 stride_shape, __private const int output_width_4, - __private const int out_channel_blocks) { + __private const int out_channel_blocks +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int inChannel +#endif +) { const int output_channel_width_idx = get_global_id(0); const int output_batch_height_idx = get_global_id(1); @@ -240,11 +253,6 @@ void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, intput_width_idx3 = select(intput_width_idx3, INT_MIN, intput_width_idx3 >= input_shape.y); #endif -#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) - const FLOAT4 dequantScaleC4 = vload4(output_channel_block_idx, dequantScale); - const FLOAT4 dequantOffsetC4 = vload4(output_channel_block_idx, dequantOffset); -#endif - int batch_index = output_batch_height_idx / output_shape.x; int input_height_block_idx = mul24((output_batch_height_idx % output_shape.x), stride_shape.x) + batch_index * input_shape.x; @@ -259,15 +267,21 @@ void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, int weight_offset = output_channel_block_idx * in_channel_block * 4 * 4; for (int in_channel_block_idx = 0; in_channel_block_idx < in_channel_block; ++in_channel_block_idx) { +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (in_channel_block_idx * 4) / blockDim * out_channel_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(output_channel_block_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); +#endif int input_width_base = in_channel_block_idx * input_shape.y; int weights_width_base = in_channel_block_idx << 2; #if (defined USE_LOW_BIT_WEIGHT_INT8) FLOAT16 weights = CONVERT_FLOAT16(vload16(0, kernel_ptr + weight_ic_offset + in_channel_block_idx * weight_oc_offset)); - FLOAT4 weights0 = CONVERT_FLOAT4(weights.s0123) * dequantScaleC4 + dequantOffsetC4; - FLOAT4 weights1 = CONVERT_FLOAT4(weights.s4567) * dequantScaleC4 + dequantOffsetC4; - FLOAT4 weights2 = CONVERT_FLOAT4(weights.s89ab) * dequantScaleC4 + dequantOffsetC4; - FLOAT4 weights3 = CONVERT_FLOAT4(weights.scdef) * dequantScaleC4 + dequantOffsetC4; + FLOAT4 weights0 = CONVERT_FLOAT4(weights.s0123) * scale0 + offset0; + FLOAT4 weights1 = CONVERT_FLOAT4(weights.s4567) * scale0 + offset0; + FLOAT4 weights2 = CONVERT_FLOAT4(weights.s89ab) * scale0 + offset0; + FLOAT4 weights3 = CONVERT_FLOAT4(weights.scdef) * scale0 + offset0; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar8 charWeightsInt4 = vload8(0, kernel_ptr + weight_ic_offset + in_channel_block_idx * weight_oc_offset); char4 charWeights0 = (char4)(0, 0, 0, 0); @@ -290,10 +304,10 @@ void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeights3.y = (charWeightsInt4.s6 & MOD_NUM) - 8; charWeights3.z = (charWeightsInt4.s7 >> 4) - 8; charWeights3.w = (charWeightsInt4.s7 & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeights0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeights1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeights2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeights3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeights0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeights1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeights2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeights3), scale0, offset0); #elif (defined USE_BUFFER) weights0 = vload4(weights_width_base, weights + weight_offset); weights1 = vload4(weights_width_base + 1, weights + weight_offset); @@ -305,6 +319,7 @@ void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights2 = RI_F(weights, SAMPLER, (int2)(weights_width_base + 2, output_channel_block_idx)); weights3 = RI_F(weights, SAMPLER, (int2)(weights_width_base + 3, output_channel_block_idx)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); in0 = RI_F(input, SAMPLER, (int2)(input_width_base + intput_width_idx0, input_height_block_idx)); in1 = RI_F(input, SAMPLER, (int2)(input_width_base + intput_width_idx1, input_height_block_idx)); in2 = RI_F(input, SAMPLER, (int2)(input_width_base + intput_width_idx2, input_height_block_idx)); @@ -359,12 +374,10 @@ __attribute__((work_group_size_hint(16, 16, 1))) void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_BUFFER) __global const FLOAT *weights, #else @@ -376,7 +389,12 @@ void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, __private const int in_channel_block, __private const int2 output_shape, __private const int2 stride_shape, __private const int output_width_4, - __private const int out_channel_blocks) { + __private const int out_channel_blocks +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int inChannel +#endif +) { const int output_channel_width_idx = get_global_id(0); const int output_batch_height_idx = get_global_id(1); @@ -420,13 +438,6 @@ void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, intput_width_idx3 = select(intput_width_idx3, INT_MIN, intput_width_idx3 >= input_shape.y); #endif -#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) - const FLOAT4 dequantScaleC03 = vload4(output_channel_idx, dequantScale); - const FLOAT4 dequantOffsetC03 = vload4(output_channel_idx, dequantOffset); - const FLOAT4 dequantScaleC47 = vload4(output_channel_idx + 1, dequantScale); - const FLOAT4 dequantOffsetC47 = vload4(output_channel_idx + 1, dequantOffset); -#endif - int batch_index = output_batch_height_idx / output_shape.x; int input_height_block_idx = mul24((output_batch_height_idx % output_shape.x), stride_shape.x) + batch_index * input_shape.x; @@ -446,6 +457,16 @@ void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, int weight_offset1 = weight_offset + in_channel_block * 4 * 4; for (int in_channel_block_idx = 0; in_channel_block_idx < in_channel_block; ++in_channel_block_idx) { +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (in_channel_block_idx * 4) / blockDim * out_channel_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(output_channel_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); + COMPUTE_FLOAT8 ScaleOffset1 = CONVERT_COMPUTE_FLOAT8(vload8(output_channel_idx + 1, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale1 = (COMPUTE_FLOAT4)(ScaleOffset1.s0, ScaleOffset1.s2, ScaleOffset1.s4, ScaleOffset1.s6); + COMPUTE_FLOAT4 offset1 = (COMPUTE_FLOAT4)(ScaleOffset1.s1, ScaleOffset1.s3, ScaleOffset1.s5, ScaleOffset1.s7); +#endif + int input_width_base = in_channel_block_idx * input_shape.y; int weights_width_base = in_channel_block_idx << 2; in0 = RI_F(input, SAMPLER, (int2)(input_width_base + intput_width_idx0, input_height_block_idx)); @@ -456,14 +477,14 @@ void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) FLOAT16 weightsInt80 = CONVERT_FLOAT16(vload16(0, kernel_ptr + weight_ic_offset + in_channel_block_idx * weight_oc_offset)); FLOAT16 weightsInt81 = CONVERT_FLOAT16(vload16(0, kernel_ptr + 16 + weight_ic_offset + in_channel_block_idx * weight_oc_offset)); - FLOAT4 weights0 = CONVERT_FLOAT4(weightsInt80.s0123) * dequantScaleC03 + dequantOffsetC03; - FLOAT4 weights1 = CONVERT_FLOAT4(weightsInt80.s4567) * dequantScaleC03 + dequantOffsetC03; - FLOAT4 weights2 = CONVERT_FLOAT4(weightsInt80.s89ab) * dequantScaleC03 + dequantOffsetC03; - FLOAT4 weights3 = CONVERT_FLOAT4(weightsInt80.scdef) * dequantScaleC03 + dequantOffsetC03; - FLOAT4 weights4 = CONVERT_FLOAT4(weightsInt81.s0123) * dequantScaleC47 + dequantOffsetC47; - FLOAT4 weights5 = CONVERT_FLOAT4(weightsInt81.s4567) * dequantScaleC47 + dequantOffsetC47; - FLOAT4 weights6 = CONVERT_FLOAT4(weightsInt81.s89ab) * dequantScaleC47 + dequantOffsetC47; - FLOAT4 weights7 = CONVERT_FLOAT4(weightsInt81.scdef) * dequantScaleC47 + dequantOffsetC47; + FLOAT4 weights0 = CONVERT_FLOAT4(weightsInt80.s0123) * scale0 + offset0; + FLOAT4 weights1 = CONVERT_FLOAT4(weightsInt80.s4567) * scale0 + offset0; + FLOAT4 weights2 = CONVERT_FLOAT4(weightsInt80.s89ab) * scale0 + offset0; + FLOAT4 weights3 = CONVERT_FLOAT4(weightsInt80.scdef) * scale0 + offset0; + FLOAT4 weights4 = CONVERT_FLOAT4(weightsInt81.s0123) * scale1 + offset1; + FLOAT4 weights5 = CONVERT_FLOAT4(weightsInt81.s4567) * scale1 + offset1; + FLOAT4 weights6 = CONVERT_FLOAT4(weightsInt81.s89ab) * scale1 + offset1; + FLOAT4 weights7 = CONVERT_FLOAT4(weightsInt81.scdef) * scale1 + offset1; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar16 charWeightsInt4 = vload16(0, kernel_ptr + weight_ic_offset + in_channel_block_idx * weight_oc_offset); char4 charWeights0 = (char4)(0, 0, 0, 0); @@ -506,14 +527,14 @@ void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeights7.y = (charWeightsInt4.se & MOD_NUM) - 8; charWeights7.z = (charWeightsInt4.sf >> 4) - 8; charWeights7.w = (charWeightsInt4.sf & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeights0), dequantScaleC03, dequantOffsetC03); - weights1 = mad(CONVERT_FLOAT4(charWeights1), dequantScaleC03, dequantOffsetC03); - weights2 = mad(CONVERT_FLOAT4(charWeights2), dequantScaleC03, dequantOffsetC03); - weights3 = mad(CONVERT_FLOAT4(charWeights3), dequantScaleC03, dequantOffsetC03); - weights4 = mad(CONVERT_FLOAT4(charWeights4), dequantScaleC47, dequantOffsetC47); - weights5 = mad(CONVERT_FLOAT4(charWeights5), dequantScaleC47, dequantOffsetC47); - weights6 = mad(CONVERT_FLOAT4(charWeights6), dequantScaleC47, dequantOffsetC47); - weights7 = mad(CONVERT_FLOAT4(charWeights7), dequantScaleC47, dequantOffsetC47); + weights0 = mad(CONVERT_FLOAT4(charWeights0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeights1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeights2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeights3), scale0, offset0); + weights4 = mad(CONVERT_FLOAT4(charWeights4), scale1, offset1); + weights5 = mad(CONVERT_FLOAT4(charWeights5), scale1, offset1); + weights6 = mad(CONVERT_FLOAT4(charWeights6), scale1, offset1); + weights7 = mad(CONVERT_FLOAT4(charWeights7), scale1, offset1); #elif (defined USE_BUFFER) weights0 = vload4(weights_width_base, weights + weight_offset); weights1 = vload4(weights_width_base + 1, weights + weight_offset); @@ -535,6 +556,8 @@ void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights6 = RI_F(weights, SAMPLER, (int2)(weights_width_base + 2, output_channel_idx + 1)); weights7 = RI_F(weights, SAMPLER, (int2)(weights_width_base + 3, output_channel_idx + 1)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); + PADZEROSVEC(in_channel_block_idx, inChannel, weights4, weights5, weights6, weights7); CALCULATE_OUTPUT(0); CALCULATE_OUTPUT(1); @@ -617,12 +640,10 @@ __attribute__((work_group_size_hint(16, 16, 1))) void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_BUFFER) __global const FLOAT *weights, #else @@ -641,7 +662,12 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, __private const int2 dilation_shape, __private const int out_width_blocks, __private const int out_channel_blocks, - __private const int out_height_blocks) { + __private const int out_height_blocks +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int inChannel +#endif +) { const int output_channel_width_idx = get_global_id(0); const int output_batch_height_idx = get_global_id(1); @@ -683,14 +709,20 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #endif #if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER) - const FLOAT4 dequantScaleC4 = vload4(out_channel_block_idx, dequantScale); - const FLOAT4 dequantOffsetC4 = vload4(out_channel_block_idx, dequantOffset); const int weight_oc_offset = out_channel_blocks * weights_shape.x * weights_shape.y * 4; #endif FLOAT4 in0, in1, in2, in3; FLOAT4 weights0, weights1, weights2, weights3; for (int in_channel_block_idx = 0; in_channel_block_idx < in_channel_block_length; ++in_channel_block_idx) { + +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (in_channel_block_idx * 4) / blockDim * out_channel_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(out_channel_block_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); +#endif + const int in_idx = mul24(in_channel_block_idx, input_shape.y); #if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER) int weight_offset = ((((4*in_channel_block_idx+0)* out_channel_blocks + out_channel_block_idx) *weights_shape.x + kh_start)*weights_shape.y + 0) * 4; @@ -712,10 +744,10 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, char4 charWeight1 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*3); - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar2 charWeightInt40 = vload2(0, kernel_ptr+weight_offset/2); @@ -742,10 +774,10 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_BUFFER) weights0 = vload4(0, weights+weight_offset); @@ -759,6 +791,7 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights2 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 2, weights_y_idx)); weights3 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 3, weights_y_idx++)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); CALCULATE_OUTPUT(0); CALCULATE_OUTPUT(1); CALCULATE_OUTPUT(2); @@ -774,10 +807,10 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, char4 charWeight1 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*3); - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar2 charWeightInt40 = vload2(0, kernel_ptr+weight_offset/2); @@ -804,10 +837,10 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_BUFFER) weights0 = vload4(0, weights+weight_offset); @@ -821,6 +854,7 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights2 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 2, weights_y_idx)); weights3 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 3, weights_y_idx++)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); CALCULATE_OUTPUT(0); CALCULATE_OUTPUT(1); CALCULATE_OUTPUT(2); @@ -838,10 +872,10 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, char4 charWeight1 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*3); - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar2 charWeightInt40 = vload2(0, kernel_ptr+weight_offset/2); @@ -868,10 +902,10 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_BUFFER) weights0 = vload4(0, weights+weight_offset); @@ -885,6 +919,7 @@ void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights2 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 2, weights_y_idx)); weights3 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 3, weights_y_idx++)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); CALCULATE_OUTPUT(0); CALCULATE_OUTPUT(1); CALCULATE_OUTPUT(2); @@ -937,12 +972,10 @@ __attribute__((work_group_size_hint(16, 16, 1))) void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_BUFFER) __global const FLOAT *weights, #else @@ -961,7 +994,12 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, __private const int2 dilation_shape, __private const int out_width_blocks, __private const int out_channel_blocks, - __private const int out_height_blocks) { + __private const int out_height_blocks +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int inChannel +#endif +) { const int output_channel_width_idx = get_global_id(0); const int output_batch_height_idx = get_global_id(1); @@ -987,10 +1025,6 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, FLOAT4 out7 = out4; #if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER) - const FLOAT4 dequantScaleC03 = vload4(out_channel_block_idx, dequantScale); - const FLOAT4 dequantOffsetC03 = vload4(out_channel_block_idx, dequantOffset); - const FLOAT4 dequantScaleC47 = vload4(out_channel_block_idx + 1, dequantScale); - const FLOAT4 dequantOffsetC47 = vload4(out_channel_block_idx + 1, dequantOffset); const int weight_oc_offset = weights_shape.x * weights_shape.y * 4; const int weight_ic_offset = out_channel_blocks * weight_oc_offset; #endif @@ -1008,6 +1042,16 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, FLOAT4 in0, in1, in2, in3; FLOAT4 weights0, weights1, weights2, weights3, weights4, weights5, weights6, weights7; for (int in_channel_block_idx = 0; in_channel_block_idx < in_channel_block_length; ++in_channel_block_idx) { +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (in_channel_block_idx * 4) / blockDim * out_channel_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(out_channel_block_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); + COMPUTE_FLOAT8 ScaleOffset1 = CONVERT_COMPUTE_FLOAT8(vload8(out_channel_block_idx + 1, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale1 = (COMPUTE_FLOAT4)(ScaleOffset1.s0, ScaleOffset1.s2, ScaleOffset1.s4, ScaleOffset1.s6); + COMPUTE_FLOAT4 offset1 = (COMPUTE_FLOAT4)(ScaleOffset1.s1, ScaleOffset1.s3, ScaleOffset1.s5, ScaleOffset1.s7); + +#endif const int in_idx = mul24(in_channel_block_idx, input_shape.y); #if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER) int weight_offset = ((((4*in_channel_block_idx+0)* out_channel_blocks + out_channel_block_idx) *weights_shape.x + 0)*weights_shape.y + 0) * 4; @@ -1033,18 +1077,18 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, char4 charWeight1 = vload4(0, kernel_ptr+weight_offset+weight_ic_offset); char4 charWeight2 = vload4(0, kernel_ptr+weight_offset+weight_ic_offset*2); char4 charWeight3 = vload4(0, kernel_ptr+weight_offset+weight_ic_offset*3); - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC03, dequantOffsetC03); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC03, dequantOffsetC03); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC03, dequantOffsetC03); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC03, dequantOffsetC03); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); charWeight0 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset); charWeight1 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset+weight_ic_offset); charWeight2 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset+weight_ic_offset*2); charWeight3 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset+weight_ic_offset*3); - weights4 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC47, dequantOffsetC47); - weights5 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC47, dequantOffsetC47); - weights6 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC47, dequantOffsetC47); - weights7 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC47, dequantOffsetC47); + weights4 = mad(CONVERT_FLOAT4(charWeight0), scale1, offset1); + weights5 = mad(CONVERT_FLOAT4(charWeight1), scale1, offset1); + weights6 = mad(CONVERT_FLOAT4(charWeight2), scale1, offset1); + weights7 = mad(CONVERT_FLOAT4(charWeight3), scale1, offset1); weight_offset += 4; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar2 charWeightInt40 = vload2(0, kernel_ptr+weight_offset/2); @@ -1071,10 +1115,10 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC03, dequantOffsetC03); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC03, dequantOffsetC03); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC03, dequantOffsetC03); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC03, dequantOffsetC03); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); charWeightInt40 = vload2(0, kernel_ptr+weight_offset/2+weight_oc_offset/2); charWeightInt41 = vload2(0, kernel_ptr+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2); charWeightInt42 = vload2(0, kernel_ptr+weight_offset/2+weight_oc_offset/2+weight_ic_offset*2/2); @@ -1099,10 +1143,10 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weights4 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC47, dequantOffsetC47); - weights5 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC47, dequantOffsetC47); - weights6 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC47, dequantOffsetC47); - weights7 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC47, dequantOffsetC47); + weights4 = mad(CONVERT_FLOAT4(charWeight0), scale1, offset1); + weights5 = mad(CONVERT_FLOAT4(charWeight1), scale1, offset1); + weights6 = mad(CONVERT_FLOAT4(charWeight2), scale1, offset1); + weights7 = mad(CONVERT_FLOAT4(charWeight3), scale1, offset1); weight_offset += 4; #elif (defined USE_BUFFER) weights0 = vload4(0, weights+weight_offset); @@ -1124,6 +1168,8 @@ void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights6 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 2, weight_size + weights_y_idx)); weights7 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 3, weight_size + weights_y_idx++)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); + PADZEROSVEC(in_channel_block_idx, inChannel, weights4, weights5, weights6, weights7); CALCULATE_OUTPUT(0); CALCULATE_OUTPUT(1); @@ -1212,12 +1258,10 @@ __attribute__((work_group_size_hint(16, 16, 1))) void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *kernel_ptr, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_BUFFER) __global const FLOAT *weights, #else @@ -1236,7 +1280,12 @@ void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, __private const int2 dilation_shape, __private const int out_width_blocks, __private const int out_channel_blocks, - __private const int out_height_blocks) { + __private const int out_height_blocks +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int inChannel +#endif +) { const int output_channel_width_idx = get_global_id(0); const int output_batch_height_idx = get_global_id(1); @@ -1269,11 +1318,15 @@ void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, FLOAT4 in0, in1, in2, in3; FLOAT4 weights0, weights1, weights2, weights3; #if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER) - const FLOAT4 dequantScaleC4 = vload4(out_channel_block_idx, dequantScale); - const FLOAT4 dequantOffsetC4 = vload4(out_channel_block_idx, dequantOffset); const int weight_oc_offset = out_channel_blocks * weights_shape.x * weights_shape.y * 4; #endif for (int in_channel_block_idx = 0; in_channel_block_idx < in_channel_block_length; ++in_channel_block_idx) { +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (in_channel_block_idx * 4) / blockDim * out_channel_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(out_channel_block_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); +#endif const int in_idx = mul24(in_channel_block_idx, input_shape.y); #if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER) int weight_offset = ((((4*in_channel_block_idx+0)* out_channel_blocks + out_channel_block_idx) *weights_shape.x + 0)*weights_shape.y + 0) * 4; @@ -1299,10 +1352,10 @@ void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, char4 charWeight1 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, kernel_ptr+weight_offset+weight_oc_offset*3); - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar2 charWeightInt40 = vload2(0, kernel_ptr+weight_offset/2); @@ -1329,10 +1382,10 @@ void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weights0 = mad(CONVERT_FLOAT4(charWeight0), dequantScaleC4, dequantOffsetC4); - weights1 = mad(CONVERT_FLOAT4(charWeight1), dequantScaleC4, dequantOffsetC4); - weights2 = mad(CONVERT_FLOAT4(charWeight2), dequantScaleC4, dequantOffsetC4); - weights3 = mad(CONVERT_FLOAT4(charWeight3), dequantScaleC4, dequantOffsetC4); + weights0 = mad(CONVERT_FLOAT4(charWeight0), scale0, offset0); + weights1 = mad(CONVERT_FLOAT4(charWeight1), scale0, offset0); + weights2 = mad(CONVERT_FLOAT4(charWeight2), scale0, offset0); + weights3 = mad(CONVERT_FLOAT4(charWeight3), scale0, offset0); weight_offset += 4; #elif (defined USE_BUFFER) weights0 = vload4(0, weights+weight_offset); @@ -1346,6 +1399,7 @@ void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input, weights2 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 2, weights_y_idx)); weights3 = RI_F(weights, SAMPLER, (int2)(weights_x_idx + 3, weights_y_idx++)); #endif + PADZEROSVEC(in_channel_block_idx, inChannel, weights0, weights1, weights2, weights3); CALCULATE_OUTPUT(0); CALCULATE_OUTPUT(1); diff --git a/source/backend/opencl/execution/cl/conv_2d_int_buf.cl b/source/backend/opencl/execution/cl/conv_2d_int_buf.cl index c2342b6d4..aeed184ce 100644 --- a/source/backend/opencl/execution/cl/conv_2d_int_buf.cl +++ b/source/backend/opencl/execution/cl/conv_2d_int_buf.cl @@ -10,7 +10,15 @@ } #define MOD_NUM 15 - +#ifdef INPUT_CHANNEL_LEAVE + #define PADZEROSVEC(k, channel, data0, data1, data2, data3) \ + data0 = (k << 2) < channel ? data0 : 0; \ + data1 = (k << 2) + 1 < channel ? data1 : 0; \ + data2 = (k << 2) + 2 < channel ? data2 : 0; \ + data3 = (k << 2) + 3 < channel ? data3 : 0; +#else + #define PADZEROSVEC(k, channel, data0, data1, data2, data3) +#endif __kernel void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS @@ -20,8 +28,7 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -34,7 +41,8 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -45,12 +53,7 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; - const float4 dequantScaleC4 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC4 = vload4(out_c_idx, dequantOffset); - - COMPUTE_FLOAT4 vbias = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT)0; - COMPUTE_FLOAT sum = (COMPUTE_FLOAT)0; + COMPUTE_FLOAT4 out0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); const int in_w_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); const int in_h_idx_base = mad24(out_h_idx, stride_hw.x, -pad_hw.x); @@ -65,6 +68,10 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS const int weight_oc_offset = out_c_blocks * filter_hw.x * filter_hw.y * 4; for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale = (COMPUTE_FLOAT4)(ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6); + COMPUTE_FLOAT4 offset = (COMPUTE_FLOAT4)(ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] int weight_offset = ((((4*in_c_idx+0)* out_c_blocks + out_c_idx) *filter_hw.x + kh_start)*filter_hw.y + kw_start) * 4; @@ -80,10 +87,10 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(filter_w_inc, weight+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(filter_w_inc, weight+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(filter_w_inc, weight+weight_offset+weight_oc_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #else uchar2 charWeightInt40 = vload2(filter_w_inc, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(filter_w_inc, weight+weight_offset/2+weight_oc_offset/2); @@ -109,12 +116,13 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #endif - sum += (in0.x + in0.y + in0.z + in0.w); + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); + out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); out0 = mad(in0.z, weight2, out0); @@ -125,8 +133,6 @@ void conv_2d_int_c4h1w1(GLOBAL_SIZE_2_DIMS } } - out0 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum) * dequantOffsetC4); - #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); #endif @@ -148,8 +154,7 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -162,7 +167,8 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks,//generate width's num __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -173,14 +179,9 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; - const float4 dequantScaleC4 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC4 = vload4(out_c_idx, dequantOffset); - - COMPUTE_FLOAT4 vbias = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out1 = out0; - COMPUTE_FLOAT sum0 = 0; - COMPUTE_FLOAT sum1 = 0; + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out0 = bias0; + COMPUTE_FLOAT4 out1 = bias0; const int in_w0_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); const int in_w1_idx_base = in_w0_idx_base + stride_hw.y; @@ -193,6 +194,10 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS const int weight_oc_offset = out_c_blocks * filter_hw.x * filter_hw.y * 4; for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale = (COMPUTE_FLOAT4)(ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6); + COMPUTE_FLOAT4 offset = (COMPUTE_FLOAT4)(ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] int weight_offset = ((((4*in_c_idx+0)* out_c_blocks + out_c_idx) *filter_hw.x + kh_start)*filter_hw.y + 0) * 4; @@ -212,10 +217,10 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(0, weight+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, weight+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, weight+weight_offset+weight_oc_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #else uchar2 charWeightInt40 = vload2(0, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(0, weight+weight_offset/2+weight_oc_offset/2); @@ -241,15 +246,13 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #endif - - sum0 += (in0.x + in0.y + in0.z + in0.w); - sum1 += (in1.x + in1.y + in1.z + in1.w); - + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); + out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); out0 = mad(in0.z, weight2, out0); @@ -265,9 +268,6 @@ void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS } } - out0 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC4); - out1 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out1) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC4); - #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); out1 = fmax(out1, (COMPUTE_FLOAT4)0); @@ -296,8 +296,7 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -310,7 +309,8 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -320,19 +320,12 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS const int out_w_idx = (out_c_w_idx % out_w_blocks) << 2; const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; - - const float4 dequantScaleC4 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC4 = vload4(out_c_idx, dequantOffset); - - COMPUTE_FLOAT4 vbias = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out1 = out0; - COMPUTE_FLOAT4 out2 = out0; - COMPUTE_FLOAT4 out3 = out0; - COMPUTE_FLOAT sum0 = 0; - COMPUTE_FLOAT sum1 = 0; - COMPUTE_FLOAT sum2 = 0; - COMPUTE_FLOAT sum3 = 0; + + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out0 = bias0; + COMPUTE_FLOAT4 out1 = bias0; + COMPUTE_FLOAT4 out2 = bias0; + COMPUTE_FLOAT4 out3 = bias0; const int in_w0_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); const int in_w1_idx_base = in_w0_idx_base + stride_hw.y; @@ -347,6 +340,10 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS const int weight_oc_offset = out_c_blocks * filter_hw.x * filter_hw.y * 4; for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale = (COMPUTE_FLOAT4)(ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6); + COMPUTE_FLOAT4 offset = (COMPUTE_FLOAT4)(ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] int weight_offset = ((((4*in_c_idx+0)* out_c_blocks + out_c_idx) *filter_hw.x + kh_start)*filter_hw.y + 0) * 4; @@ -370,10 +367,10 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(0, weight+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, weight+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, weight+weight_offset+weight_oc_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #else uchar2 charWeightInt40 = vload2(0, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(0, weight+weight_offset/2+weight_oc_offset/2); @@ -399,16 +396,12 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #endif - - sum0 += (in0.x + in0.y + in0.z + in0.w); - sum1 += (in1.x + in1.y + in1.z + in1.w); - sum2 += (in2.x + in2.y + in2.z + in2.w); - sum3 += (in3.x + in3.y + in3.z + in3.w); + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); @@ -434,10 +427,7 @@ void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS } } } - out0 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC4); - out1 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out1) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC4); - out2 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out2) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum2) * dequantOffsetC4); - out3 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out3) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum3) * dequantOffsetC4); + #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); out1 = fmax(out1, (COMPUTE_FLOAT4)0); @@ -479,8 +469,7 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -493,7 +482,8 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -504,18 +494,11 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS const int out_b_idx = out_b_h_idx / out_h_blocks;//equal to in_b_idx const int out_h_idx = (out_b_h_idx % out_h_blocks) << 2; - const float4 dequantScaleC4 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC4 = vload4(out_c_idx, dequantOffset); - - COMPUTE_FLOAT4 vbias = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out1 = out0; - COMPUTE_FLOAT4 out2 = out0; - COMPUTE_FLOAT4 out3 = out0; - COMPUTE_FLOAT sum0 = 0; - COMPUTE_FLOAT sum1 = 0; - COMPUTE_FLOAT sum2 = 0; - COMPUTE_FLOAT sum3 = 0; + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out0 = bias0; + COMPUTE_FLOAT4 out1 = bias0; + COMPUTE_FLOAT4 out2 = bias0; + COMPUTE_FLOAT4 out3 = bias0; const int in_w_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); @@ -531,6 +514,10 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS const int weight_oc_offset = out_c_blocks * filter_hw.x * filter_hw.y * 4; const int in_hw_size = in_hw.x * in_hw.y; for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale = (COMPUTE_FLOAT4)(ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6); + COMPUTE_FLOAT4 offset = (COMPUTE_FLOAT4)(ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] const int inp_offset_base = (out_b_idx * in_c_blocks + in_c_idx) * in_hw.x * in_hw.y * 4; @@ -553,10 +540,10 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(0, weight+weight_offset+weight_oc_offset); char4 charWeight2 = vload4(0, weight+weight_offset+weight_oc_offset*2); char4 charWeight3 = vload4(0, weight+weight_offset+weight_oc_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #else uchar2 charWeightInt40 = vload2(0, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(0, weight+weight_offset/2+weight_oc_offset/2); @@ -582,16 +569,12 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale + offset; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale + offset; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale + offset; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale + offset; #endif - - sum0 += (in0.x + in0.y + in0.z + in0.w); - sum1 += (in1.x + in1.y + in1.z + in1.w); - sum2 += (in2.x + in2.y + in2.z + in2.w); - sum3 += (in3.x + in3.y + in3.z + in3.w); + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); @@ -617,12 +600,7 @@ void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS } } } - - out0 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC4); - out1 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out1) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC4); - out2 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out2) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum2) * dequantOffsetC4); - out3 = vbias + CONVERT_COMPUTE_FLOAT4(convert_float4(out3) * dequantScaleC4 + convert_float4((COMPUTE_FLOAT4)sum3) * dequantOffsetC4); - + #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); out1 = fmax(out1, (COMPUTE_FLOAT4)0); @@ -671,8 +649,7 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -685,7 +662,8 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -696,25 +674,16 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS const int out_b_idx = out_b_h_idx / out_h_blocks;//equal to in_b_idx const int out_h_idx = (out_b_h_idx % out_h_blocks) << 2; - const float4 dequantScaleC03 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC03 = vload4(out_c_idx, dequantOffset); - const float4 dequantScaleC47 = vload4(out_c_idx + 1, dequantScale); - const float4 dequantOffsetC47 = vload4(out_c_idx + 1, dequantOffset); - - COMPUTE_FLOAT4 vbias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out1 = out0; - COMPUTE_FLOAT4 out2 = out0; - COMPUTE_FLOAT4 out3 = out0; - COMPUTE_FLOAT4 vbias1 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx + 1, bias)); - COMPUTE_FLOAT4 out4 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out5 = out0; - COMPUTE_FLOAT4 out6 = out0; - COMPUTE_FLOAT4 out7 = out0; - COMPUTE_FLOAT sum0 = 0; - COMPUTE_FLOAT sum1 = 0; - COMPUTE_FLOAT sum2 = 0; - COMPUTE_FLOAT sum3 = 0; + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out0 = bias0; + COMPUTE_FLOAT4 out1 = bias0; + COMPUTE_FLOAT4 out2 = bias0; + COMPUTE_FLOAT4 out3 = bias0; + COMPUTE_FLOAT4 bias1 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx + 1, bias)); + COMPUTE_FLOAT4 out4 = bias1; + COMPUTE_FLOAT4 out5 = bias1; + COMPUTE_FLOAT4 out6 = bias1; + COMPUTE_FLOAT4 out7 = bias1; const int in_w_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); @@ -731,6 +700,13 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS const int weight_ic_offset = out_c_blocks * weight_oc_offset; const int in_hw_size = in_hw.x * in_hw.y; for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT8 ScaleOffset1 = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx + 1, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); + COMPUTE_FLOAT4 scale1 = (COMPUTE_FLOAT4)(ScaleOffset1.s0, ScaleOffset1.s2, ScaleOffset1.s4, ScaleOffset1.s6); + COMPUTE_FLOAT4 offset1 = (COMPUTE_FLOAT4)(ScaleOffset1.s1, ScaleOffset1.s3, ScaleOffset1.s5, ScaleOffset1.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] const int inp_offset_base = (out_b_idx * in_c_blocks + in_c_idx) * in_hw.x * in_hw.y * 4; @@ -753,10 +729,10 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(0, weight+weight_offset+weight_ic_offset); char4 charWeight2 = vload4(0, weight+weight_offset+weight_ic_offset*2); char4 charWeight3 = vload4(0, weight+weight_offset+weight_ic_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale0 + offset0; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale0 + offset0; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale0 + offset0; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale0 + offset0; #else uchar2 charWeightInt40 = vload2(0, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(0, weight+weight_offset/2+weight_ic_offset/2); @@ -782,16 +758,12 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale0 + offset0; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale0 + offset0; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale0 + offset0; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale0 + offset0; #endif - - sum0 += (in0.x + in0.y + in0.z + in0.w); - sum1 += (in1.x + in1.y + in1.z + in1.w); - sum2 += (in2.x + in2.y + in2.z + in2.w); - sum3 += (in3.x + in3.y + in3.z + in3.w); + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); @@ -818,10 +790,10 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS charWeight1 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset); charWeight2 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset*2); charWeight3 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset*3); - weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale1 + offset1; + weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale1 + offset1; + weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale1 + offset1; + weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale1 + offset1; #else charWeightInt40 = vload2(0, weight+weight_offset/2+weight_oc_offset/2); charWeightInt41 = vload2(0, weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2); @@ -847,11 +819,12 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale1 + offset1; + weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale1 + offset1; + weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale1 + offset1; + weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale1 + offset1; #endif + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out4 = mad(in0.x, weight0, out4); out4 = mad(in0.y, weight1, out4); @@ -878,15 +851,6 @@ void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS } } - out0 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC03); - out1 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out1) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC03); - out2 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out2) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum2) * dequantOffsetC03); - out3 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out3) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum3) * dequantOffsetC03); - out4 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out4) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC47); - out5 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out5) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC47); - out6 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out6) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum2) * dequantOffsetC47); - out7 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out7) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum3) * dequantOffsetC47); - #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); out1 = fmax(out1, (COMPUTE_FLOAT4)0); @@ -974,8 +938,7 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -988,7 +951,8 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -998,20 +962,13 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS const int out_w_idx = out_c_w_idx % out_w_blocks; const int out_b_idx = out_b_h_idx / out_h_blocks;//equal to in_b_idx const int out_h_idx = (out_b_h_idx % out_h_blocks) << 1; - - const float4 dequantScaleC03 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC03 = vload4(out_c_idx, dequantOffset); - const float4 dequantScaleC47 = vload4(out_c_idx + 1, dequantScale); - const float4 dequantOffsetC47 = vload4(out_c_idx + 1, dequantOffset); - - COMPUTE_FLOAT4 vbias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out1 = out0; - COMPUTE_FLOAT4 vbias1 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx + 1, bias)); - COMPUTE_FLOAT4 out2 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out3 = out0; - COMPUTE_FLOAT sum0 = 0; - COMPUTE_FLOAT sum1 = 0; + + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out0 = bias0; + COMPUTE_FLOAT4 out1 = bias0; + COMPUTE_FLOAT4 bias1 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx + 1, bias)); + COMPUTE_FLOAT4 out2 = bias1; + COMPUTE_FLOAT4 out3 = bias1; const int in_w_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); @@ -1027,6 +984,13 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS const int in_hw_size = in_hw.x * in_hw.y; // weight: [ic/4, oc, 4], loop: ic/4 for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT8 ScaleOffset1 = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx + 1, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); + COMPUTE_FLOAT4 scale1 = (COMPUTE_FLOAT4)(ScaleOffset1.s0, ScaleOffset1.s2, ScaleOffset1.s4, ScaleOffset1.s6); + COMPUTE_FLOAT4 offset1 = (COMPUTE_FLOAT4)(ScaleOffset1.s1, ScaleOffset1.s3, ScaleOffset1.s5, ScaleOffset1.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] const int inp_offset_base = (out_b_idx * in_c_blocks + in_c_idx) * in_hw.x * in_hw.y * 4; @@ -1044,10 +1008,10 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(0, weight+weight_offset+weight_ic_offset); char4 charWeight2 = vload4(0, weight+weight_offset+weight_ic_offset*2); char4 charWeight3 = vload4(0, weight+weight_offset+weight_ic_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale0 + offset0; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale0 + offset0; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale0 + offset0; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale0 + offset0; #else uchar2 charWeightInt40 = vload2(0, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(0, weight+weight_offset/2+weight_ic_offset/2); @@ -1073,15 +1037,12 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale0 + offset0; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale0 + offset0; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale0 + offset0; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale0 + offset0; #endif - - sum0 += (in0.x + in0.y + in0.z + in0.w); - sum1 += (in1.x + in1.y + in1.z + in1.w); - + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); out0 = mad(in0.z, weight2, out0); @@ -1097,10 +1058,10 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS charWeight1 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset); charWeight2 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset*2); charWeight3 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset*3); - weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale1 + offset1; + weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale1 + offset1; + weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale1 + offset1; + weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale1 + offset1; #else charWeightInt40 = vload2(0, weight+weight_offset/2+weight_oc_offset/2); charWeightInt41 = vload2(0, weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2); @@ -1126,11 +1087,12 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0& MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1& MOD_NUM) - 8; - weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); -#endif + weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale1 + offset1; + weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale1 + offset1; + weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale1 + offset1; + weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale1 + offset1; +#endif + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out2 = mad(in0.x, weight0, out2); out2 = mad(in0.y, weight1, out2); out2 = mad(in0.z, weight2, out2); @@ -1146,11 +1108,6 @@ void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS } } - out0 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC03); - out1 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out1) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC03); - out2 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out2) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC47); - out3 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out3) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC47); - #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); out1 = fmax(out1, (COMPUTE_FLOAT4)0); @@ -1208,8 +1165,7 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS #else __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT *output, __private const int2 in_hw, @@ -1222,7 +1178,8 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS __private const int2 dilate_hw, __private const int out_w_blocks, __private const int out_c_blocks, - __private const int out_h_blocks) { + __private const int out_h_blocks, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -1233,25 +1190,16 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS const int out_b_idx = out_b_h_idx / out_hw.x;//equal to in_b_idx const int out_h_idx = out_b_h_idx % out_hw.x; - const float4 dequantScaleC03 = vload4(out_c_idx, dequantScale); - const float4 dequantOffsetC03 = vload4(out_c_idx, dequantOffset); - const float4 dequantScaleC47 = vload4(out_c_idx + 1, dequantScale); - const float4 dequantOffsetC47 = vload4(out_c_idx + 1, dequantOffset); - - COMPUTE_FLOAT4 vbias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT4 out0 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out1 = out0; - COMPUTE_FLOAT4 out2 = out0; - COMPUTE_FLOAT4 out3 = out0; - COMPUTE_FLOAT4 vbias1 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx + 1, bias)); - COMPUTE_FLOAT4 out4 = (COMPUTE_FLOAT4)0; - COMPUTE_FLOAT4 out5 = out0; - COMPUTE_FLOAT4 out6 = out0; - COMPUTE_FLOAT4 out7 = out0; - COMPUTE_FLOAT sum0 = 0; - COMPUTE_FLOAT sum1 = 0; - COMPUTE_FLOAT sum2 = 0; - COMPUTE_FLOAT sum3 = 0; + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out0 = bias0; + COMPUTE_FLOAT4 out1 = bias0; + COMPUTE_FLOAT4 out2 = bias0; + COMPUTE_FLOAT4 out3 = bias0; + COMPUTE_FLOAT4 bias1 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx + 1, bias)); + COMPUTE_FLOAT4 out4 = bias1; + COMPUTE_FLOAT4 out5 = bias1; + COMPUTE_FLOAT4 out6 = bias1; + COMPUTE_FLOAT4 out7 = bias1; const int in_w0_idx_base = mad24(out_w_idx, stride_hw.y, -pad_hw.y); const int in_w1_idx_base = in_w0_idx_base + stride_hw.y; @@ -1267,6 +1215,13 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS const int weight_oc_offset = filter_hw.x * filter_hw.y * 4; const int weight_ic_offset = out_c_blocks * weight_oc_offset; for(ushort in_c_idx = 0; in_c_idx < in_c_blocks; in_c_idx++) { + int kindex = (in_c_idx * 4) / blockDim * out_c_blocks * 8; + COMPUTE_FLOAT8 ScaleOffset0 = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + COMPUTE_FLOAT8 ScaleOffset1 = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx + 1, dequantScaleOffset + kindex)); + COMPUTE_FLOAT4 scale0 = (COMPUTE_FLOAT4)(ScaleOffset0.s0, ScaleOffset0.s2, ScaleOffset0.s4, ScaleOffset0.s6); + COMPUTE_FLOAT4 offset0 = (COMPUTE_FLOAT4)(ScaleOffset0.s1, ScaleOffset0.s3, ScaleOffset0.s5, ScaleOffset0.s7); + COMPUTE_FLOAT4 scale1 = (COMPUTE_FLOAT4)(ScaleOffset1.s0, ScaleOffset1.s2, ScaleOffset1.s4, ScaleOffset1.s6); + COMPUTE_FLOAT4 offset1 = (COMPUTE_FLOAT4)(ScaleOffset1.s1, ScaleOffset1.s3, ScaleOffset1.s5, ScaleOffset1.s7); //weights NC4HW4 [1, 4*icC4, ocC4*kh*kw, 1] xic4 //index: [0, 4*in_c_idx, out_c_idx*kh*kw + kh_start*kw + kw_start, 0] int weight_offset = ((((4*in_c_idx+0)* out_c_blocks + out_c_idx) *filter_hw.x + kh_start)*filter_hw.y + 0) * 4; @@ -1290,10 +1245,10 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS char4 charWeight1 = vload4(0, weight+weight_offset+weight_ic_offset); char4 charWeight2 = vload4(0, weight+weight_offset+weight_ic_offset*2); char4 charWeight3 = vload4(0, weight+weight_offset+weight_ic_offset*3); - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale0 + offset0; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale0 + offset0; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale0 + offset0; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale0 + offset0; #else uchar2 charWeightInt40 = vload2(0, weight+weight_offset/2); uchar2 charWeightInt41 = vload2(0, weight+weight_offset/2+weight_ic_offset/2); @@ -1319,16 +1274,12 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + COMPUTE_FLOAT4 weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale0 + offset0; + COMPUTE_FLOAT4 weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale0 + offset0; + COMPUTE_FLOAT4 weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale0 + offset0; + COMPUTE_FLOAT4 weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale0 + offset0; #endif - - sum0 += (in0.x + in0.y + in0.z + in0.w); - sum1 += (in1.x + in1.y + in1.z + in1.w); - sum2 += (in2.x + in2.y + in2.z + in2.w); - sum3 += (in3.x + in3.y + in3.z + in3.w); + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out0 = mad(in0.x, weight0, out0); out0 = mad(in0.y, weight1, out0); @@ -1355,10 +1306,10 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS charWeight1 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset); charWeight2 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset*2); charWeight3 = vload4(0, weight+weight_offset+weight_oc_offset+weight_ic_offset*3); - weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale1 + offset1; + weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale1 + offset1; + weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale1 + offset1; + weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale1 + offset1; #else charWeightInt40 = vload2(0, weight+weight_offset/2+weight_oc_offset/2); charWeightInt41 = vload2(0, weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2); @@ -1384,11 +1335,12 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS charWeight3.y = (charWeightInt43.s0 & MOD_NUM) - 8; charWeight3.z = (charWeightInt43.s1 >> 4) - 8; charWeight3.w = (charWeightInt43.s1 & MOD_NUM) - 8; - weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0); - weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1); - weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2); - weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3); + weight0 = CONVERT_COMPUTE_FLOAT4(charWeight0) * scale1 + offset1; + weight1 = CONVERT_COMPUTE_FLOAT4(charWeight1) * scale1 + offset1; + weight2 = CONVERT_COMPUTE_FLOAT4(charWeight2) * scale1 + offset1; + weight3 = CONVERT_COMPUTE_FLOAT4(charWeight3) * scale1 + offset1; #endif + PADZEROSVEC(in_c_idx, inChannel, weight0, weight1, weight2, weight3); out4 = mad(in0.x, weight0, out4); out4 = mad(in0.y, weight1, out4); @@ -1415,15 +1367,6 @@ void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS } } - out0 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out0) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC03); - out1 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out1) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC03); - out2 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out2) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum2) * dequantOffsetC03); - out3 = vbias0 + CONVERT_COMPUTE_FLOAT4(convert_float4(out3) * dequantScaleC03 + convert_float4((COMPUTE_FLOAT4)sum3) * dequantOffsetC03); - out4 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out4) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum0) * dequantOffsetC47); - out5 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out5) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum1) * dequantOffsetC47); - out6 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out6) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum2) * dequantOffsetC47); - out7 = vbias1 + CONVERT_COMPUTE_FLOAT4(convert_float4(out7) * dequantScaleC47 + convert_float4((COMPUTE_FLOAT4)sum3) * dequantOffsetC47); - #ifdef RELU out0 = fmax(out0, (COMPUTE_FLOAT4)0); out1 = fmax(out1, (COMPUTE_FLOAT4)0); diff --git a/source/backend/opencl/execution/cl/gemm.cl b/source/backend/opencl/execution/cl/gemm.cl index a3ec5d516..eb2d9e19f 100644 --- a/source/backend/opencl/execution/cl/gemm.cl +++ b/source/backend/opencl/execution/cl/gemm.cl @@ -277,16 +277,24 @@ __kernel void gemmWinogradW2(__read_only image2d_t uInput, __read_only image2d_t } } +#ifdef INPUT_CHANNEL_LEAVE + #define PADZEROSVEC(k, channel, data0, data1, data2, data3) \ + data0 = (k << 2) < channel ? data0 : 0; \ + data1 = (k << 2) + 1 < channel ? data1 : 0; \ + data2 = (k << 2) + 2 < channel ? data2 : 0; \ + data3 = (k << 2) + 3 < channel ? data3 : 0; +#else + #define PADZEROSVEC(k, channel, data0, data1, data2, data3) +#endif + __kernel void gemm_conv(GLOBAL_SIZE_DIM2 __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *weight, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #else __global const FLOAT *weight, #endif @@ -294,13 +302,16 @@ __kernel void gemm_conv(GLOBAL_SIZE_DIM2 __write_only image2d_t output, __private const int dstChannelC4, __private const int srcChannelC4, - __private const int batch) { + __private const int batch +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int srcChannel +#endif +) { int2 pos = (int2)(get_global_id(0), get_global_id(1)); //cout/4, b UNIFORM_BOUNDRY_CHECK(pos.x, pos.y); - FLOAT4 bias0 = RI_F(bias, SAMPLER, (int2)(pos.x, 0)); - FLOAT sum = 0; - FLOAT4 out = 0; + FLOAT4 out = RI_F(bias, SAMPLER, (int2)(pos.x, 0)); #if (defined USE_LOW_BIT_WEIGHT_INT8) int weight_offset = pos.x * 16; @@ -312,17 +323,23 @@ __kernel void gemm_conv(GLOBAL_SIZE_DIM2 int weight_offset = pos.x * 16; int weight_oc_offset = dstChannelC4 * 16; #endif - -#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) - const FLOAT4 Scale = vload4(pos.x, dequantScale); - const FLOAT4 Offset = vload4(pos.x, dequantOffset); -#endif for (int k = 0; k < srcChannelC4; ++k) { +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (k * 4) / blockDim * dstChannelC4 * 8; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(pos.x, dequantScaleOffset + kindex)); + COMPUTE_FLOAT16 scale = (COMPUTE_FLOAT16)(ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6, + ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6, + ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6, + ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6); + COMPUTE_FLOAT16 offset = (COMPUTE_FLOAT16)(ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7, + ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7, + ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7, + ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7); +#endif FLOAT4 in = RI_F(input, SAMPLER, (int2)(k, pos.y)); #if (defined USE_LOW_BIT_WEIGHT_INT8) - FLOAT16 weights = CONVERT_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); - sum += in.x + in.y + in.z + in.w; + FLOAT16 weights = CONVERT_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * scale + offset; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); char16 charWeights = 0; @@ -342,12 +359,12 @@ __kernel void gemm_conv(GLOBAL_SIZE_DIM2 charWeights.sd = (charWeightsInt4.s6 & 15) - 8; charWeights.se = (charWeightsInt4.s7 >> 4) - 8; charWeights.sf = (charWeightsInt4.s7 & 15) - 8; - FLOAT16 weights = CONVERT_FLOAT16(charWeights); - sum += in.x + in.y + in.z + in.w; + FLOAT16 weights = CONVERT_FLOAT16(charWeights) * scale + offset; #else FLOAT16 weights = vload16(0, weight + weight_offset + k * weight_oc_offset); #endif + PADZEROSVEC(k, srcChannel, weights.s0123, weights.s4567, weights.s89ab, weights.scdef); out = mad((FLOAT4)in.x, (FLOAT4)weights.s0123, out); out = mad((FLOAT4)in.y, (FLOAT4)weights.s4567, out); @@ -355,9 +372,6 @@ __kernel void gemm_conv(GLOBAL_SIZE_DIM2 out = mad((FLOAT4)in.w, (FLOAT4)weights.scdef, out); } -#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) - out = bias0 + mad(out, Scale, sum * Offset); -#endif #ifdef RELU out = fmax(out, (FLOAT4)0); #endif @@ -373,12 +387,10 @@ __kernel void gemm_conv_b2(GLOBAL_SIZE_DIM2 __read_only image2d_t input, #if (defined USE_LOW_BIT_WEIGHT_INT8) __global const char *weight, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, - __global const FLOAT *dequantScale, - __global const FLOAT *dequantOffset, + __global const float *dequantScaleOffset, #else __global const FLOAT *weight, #endif @@ -386,15 +398,19 @@ __kernel void gemm_conv_b2(GLOBAL_SIZE_DIM2 __write_only image2d_t output, __private const int dstChannelC4, __private const int srcChannelC4, - __private const int batch) { + __private const int batch +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + ,__private const int blockDim + ,__private const int srcChannel +#endif +) { int2 pos = (int2)(get_global_id(0), get_global_id(1)); //cout/4, b UNIFORM_BOUNDRY_CHECK(pos.x, pos.y); int pos_x = pos.x << 2; int pos_y = pos.y << 1; FLOAT4 bias0 = RI_F(bias, SAMPLER, (int2)(pos.x, 0)); - FLOAT sum0 = 0, sum1 = 0; - FLOAT4 out0 = (FLOAT4)0, out1 = (FLOAT4)0; + FLOAT4 out0 = bias0, out1 = bias0; #if (defined USE_LOW_BIT_WEIGHT_INT8) int weight_offset = pos.x * 16; @@ -406,19 +422,24 @@ __kernel void gemm_conv_b2(GLOBAL_SIZE_DIM2 int weight_offset = pos.x * 16; int weight_oc_offset = dstChannelC4 * 16; #endif - -#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) - const FLOAT4 Scale = vload4(pos.x, dequantScale); - const FLOAT4 Offset = vload4(pos.x, dequantOffset); -#endif for (int k = 0; k < srcChannelC4; ++k) { +#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) + int kindex = (k * 4) / blockDim * dstChannelC4 * 8; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(pos.x, dequantScaleOffset + kindex)); + COMPUTE_FLOAT16 scale = (COMPUTE_FLOAT16)(ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6, + ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6, + ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6, + ScaleOffset.s0, ScaleOffset.s2, ScaleOffset.s4, ScaleOffset.s6); + COMPUTE_FLOAT16 offset = (COMPUTE_FLOAT16)(ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7, + ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7, + ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7, + ScaleOffset.s1, ScaleOffset.s3, ScaleOffset.s5, ScaleOffset.s7); +#endif FLOAT4 in0 = RI_F(input, SAMPLER, (int2)(k, pos_y)); FLOAT4 in1 = RI_F(input, SAMPLER, (int2)(k, pos_y + 1)); #if (defined USE_LOW_BIT_WEIGHT_INT8) - FLOAT16 weights = CONVERT_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); - sum0 += in0.x + in0.y + in0.z + in0.w; - sum1 += in1.x + in1.y + in1.z + in1.w; + FLOAT16 weights = CONVERT_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * scale + offset; #elif (defined USE_LOW_BIT_WEIGHT_INT4) uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); char16 charWeights = 0; @@ -438,12 +459,11 @@ __kernel void gemm_conv_b2(GLOBAL_SIZE_DIM2 charWeights.sd = (charWeightsInt4.s6 & 15) - 8; charWeights.se = (charWeightsInt4.s7 >> 4) - 8; charWeights.sf = (charWeightsInt4.s7 & 15) - 8; - FLOAT16 weights = CONVERT_FLOAT16(charWeights); - sum0 += in0.x + in0.y + in0.z + in0.w; - sum1 += in1.x + in1.y + in1.z + in1.w; + FLOAT16 weights = CONVERT_FLOAT16(charWeights) * scale + offset; #else FLOAT16 weights = vload16(0, weight + weight_offset + k * weight_oc_offset); #endif + PADZEROSVEC(k, srcChannel, weights.s0123, weights.s4567, weights.s89ab, weights.scdef); out0 = mad((FLOAT4)in0.x, (FLOAT4)weights.s0123, out0); out0 = mad((FLOAT4)in0.y, (FLOAT4)weights.s4567, out0); @@ -455,10 +475,6 @@ __kernel void gemm_conv_b2(GLOBAL_SIZE_DIM2 out1 = mad((FLOAT4)in1.z, (FLOAT4)weights.s89ab, out1); out1 = mad((FLOAT4)in1.w, (FLOAT4)weights.scdef, out1); } -#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) - out0 = bias0 + mad(out0, Scale, sum0 * Offset); - out1 = bias0 + mad(out1, Scale, sum1 * Offset); -#endif #ifdef RELU out0 = fmax(out0, (FLOAT4)0); out1 = fmax(out1, (FLOAT4)0); diff --git a/source/backend/opencl/execution/cl/gemm_quant_batch_buf.cl b/source/backend/opencl/execution/cl/gemm_quant_batch_buf.cl new file mode 100644 index 000000000..3fc8fd050 --- /dev/null +++ b/source/backend/opencl/execution/cl/gemm_quant_batch_buf.cl @@ -0,0 +1,780 @@ +#ifdef MNN_SUPPORT_FP16 +#pragma OPENCL EXTENSION cl_khr_fp16 : enable +#endif + +#define GLOBAL_SIZE_DIM2 \ + __private int global_size_dim0, __private int global_size_dim1, + +#define UNIFORM_BOUNDRY_CHECK(index0, index1) \ + if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { \ + return; \ + } + +#define GLOBAL_SIZE_DIM3 \ + __private int global_size_dim0, __private int global_size_dim1, __private int global_size_dim2, + +#define UNIFORM_BOUNDRY_CHECK3(index0, index1, index2) \ + if(index0 >= global_size_dim0 || index1 >= global_size_dim1 || index2 >= global_size_dim2) { \ + return; \ + } + +#define UCHAR16_TO_2CHAR16(a, b, c) \ + a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; \ + a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; \ + b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; \ + b.s8 = (c.sc >> 4) - 8; b.s9 = (c.sc & 15) - 8; b.sa = (c.sd >> 4) - 8; b.sb = (c.sd & 15) - 8; b.sc = (c.se >> 4) - 8; b.sd = (c.se & 15) - 8; b.se = (c.sf >> 4) - 8; b.sf = (c.sf & 15) - 8; + +#define UCHAR8_TO_CHAR16(a, c) \ + a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; \ + a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; + +#define DOT16X16(a, b, c) \ + c += dot(a.s0123, b.s0123); \ + c += dot(a.s4567, b.s4567); \ + c += dot(a.s89ab, b.s89ab); \ + c += dot(a.scdef, b.scdef); + +__constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST; + +__kernel void reshape_nchw4_nhwc4(GLOBAL_SIZE_DIM3 +__global const FLOAT* input, +__global FLOAT* output, +__private const int width_height, +__private const int batch, +__private const int channel, +__private const int channelC4){ + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + const int wh = get_global_id(2); // w*h + + UNIFORM_BOUNDRY_CHECK3(x, y, wh); + + const int x4 = x << 2; + const int y4 = y << 2; + const int channel4 = channelC4 * 4; + const int stride = channel4 * width_height; + const int input_offset = (y4 * channel4 + x4) * width_height + wh * 4; + const int output_offset = ((y * width_height + wh) * channel4 + x4) * 4; + FLOAT4 in0 = vload4(0, input + input_offset); + FLOAT4 in1 = (y4 + 1 < batch) ? vload4(0, input + input_offset + stride) : (FLOAT4)0; + FLOAT4 in2 = (y4 + 2 < batch) ? vload4(0, input + input_offset + 2 * stride) : (FLOAT4)0; + FLOAT4 in3 = (y4 + 3 < batch) ? vload4(0, input + input_offset + 3 * stride) : (FLOAT4)0; + +#ifdef INPUT_CHANNEL_LEAVE + if(x4 + 3 >= channel){ + FLOAT *in0_ptr = (FLOAT*)&in0; + FLOAT *in1_ptr = (FLOAT*)&in1; + FLOAT *in2_ptr = (FLOAT*)&in2; + FLOAT *in3_ptr = (FLOAT*)&in3; + int remain = x4 + 3 - channel; + for(int i = remain; i >= 0; i--){ + in0_ptr[3 - remain] = 0; + in1_ptr[3 - remain] = 0; + in2_ptr[3 - remain] = 0; + in3_ptr[3 - remain] = 0; + } + } +#endif + + FLOAT16 out = (FLOAT16)(in0.s0, in1.s0, in2.s0, in3.s0, in0.s1, in1.s1, in2.s1, in3.s1, in0.s2, in1.s2, in2.s2, in3.s2, in0.s3, in1.s3, in2.s3, in3.s3); + + vstore16(out, 0, output+output_offset); +} + +__kernel void reshape_nhwc4_nchw4(GLOBAL_SIZE_DIM3 +__global const FLOAT* input, +__global FLOAT* output, +__private const int width_height, +__private const int batch, +__private const int channelC4){ + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + const int wh = get_global_id(2); //w*h + + UNIFORM_BOUNDRY_CHECK3(x, y, wh); + + const int x4 = x << 2; + const int y4 = y << 2; + const int channel4 = channelC4 * 4; + const int stride = channel4 * width_height; + const int input_offset = ((y * width_height + wh) * channel4 + x4) * 4; + const int output_offset = (y4 * channel4 + x4) * width_height + wh * 4; + FLOAT16 in = vload16(0, input + input_offset); + + FLOAT4 out0 = (FLOAT4)(in.s0, in.s4, in.s8, in.sc); + FLOAT4 out1 = (FLOAT4)(in.s1, in.s5, in.s9, in.sd); + FLOAT4 out2 = (FLOAT4)(in.s2, in.s6, in.sa, in.se); + FLOAT4 out3 = (FLOAT4)(in.s3, in.s7, in.sb, in.sf); + + vstore4(out0, 0, output+output_offset); + if(y4 + 1 >= batch) return; + vstore4(out1, 0, output+output_offset+stride); + if(y4 + 2 >= batch) return; + vstore4(out2, 0, output+output_offset+2*stride); + if(y4 + 3 >= batch) return; + vstore4(out3, 0, output+output_offset+3*stride); +} + + +__kernel void gemm_b4_c4_buf(GLOBAL_SIZE_DIM2 + __global const FLOAT* input, +#if (defined USE_LOW_BIT_WEIGHT_INT8) + __global const char *weight, +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + __global const uchar *weight, +#endif + __global const float *dequantScaleOffset, + __global const FLOAT *bias, + __global FLOAT* output, + __private const int dstChannelC4, + __private const int srcChannelC4, + __private const int blockNum, + __private const int blockDim) { + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + + UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_c_idx = x; + const int out_b_idx = y << 2; + + COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); + COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0.s0; + COMPUTE_FLOAT4 out1 = (COMPUTE_FLOAT4)bias0.s1, out2 = (COMPUTE_FLOAT4)bias0.s2, out3 = (COMPUTE_FLOAT4)bias0.s3; + + int input_offset = out_b_idx * srcChannelC4 * 4; + int out_offset = (out_b_idx * dstChannelC4 + out_c_idx * 4) * 4; + +#if (defined USE_LOW_BIT_WEIGHT_INT4) + int weight_offset = out_c_idx * 4 * 8; + int weight_oc_offset = dstChannelC4 * 32; +#else + int weight_offset = out_c_idx * 4 * 16; + int weight_oc_offset = dstChannelC4 * 64; +#endif + + const int loop = (blockDim + 15) / 16; +#ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*16; +#else + const int loop_end = loop; +#endif + + for (int i = 0; i < blockNum; i++){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; +#if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; + weights2 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 32)) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 48)) * ScaleOffset.s6 + ScaleOffset.s7; +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt40 = vload16(0, weight + weight_offset + k * weight_oc_offset); + uchar16 charWeightsInt41 = vload16(0, weight + weight_offset + k * weight_oc_offset + 16); + { + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; + } + } +#endif + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + COMPUTE_FLOAT *weights2_ptr = (COMPUTE_FLOAT *)&weights2; + COMPUTE_FLOAT *weights3_ptr = (COMPUTE_FLOAT *)&weights3; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights1_ptr[i], out1); + out2 = mad(in, weights2_ptr[i], out2); + out3 = mad(in, weights3_ptr[i], out3); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; +#if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; + weights2 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 32)) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 48)) * ScaleOffset.s6 + ScaleOffset.s7; +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt40 = vload16(0, weight + weight_offset + k * weight_oc_offset); + uchar16 charWeightsInt41 = vload16(0, weight + weight_offset + k * weight_oc_offset + 16); + { + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; + } + } +#endif + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + COMPUTE_FLOAT *weights2_ptr = (COMPUTE_FLOAT *)&weights2; + COMPUTE_FLOAT *weights3_ptr = (COMPUTE_FLOAT *)&weights3; + for (int i = 0; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights1_ptr[i], out1); + out2 = mad(in, weights2_ptr[i], out2); + out3 = mad(in, weights3_ptr[i], out3); + } + } +#endif + } +#ifdef RELU + out = fmax(out, (COMPUTE_FLOAT4)0); + out1 = fmax(out1, (COMPUTE_FLOAT4)0); + out2 = fmax(out2, (COMPUTE_FLOAT4)0); + out3 = fmax(out3, (COMPUTE_FLOAT4)0); +#endif + +#ifdef RELU6 + out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out1 = clamp(out1, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out2 = clamp(out2, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out3 = clamp(out3, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); +#endif + + vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out1), 0, output+out_offset + 4); + vstore4(CONVERT_FLOAT4(out2), 0, output+out_offset + 8); + vstore4(CONVERT_FLOAT4(out3), 0, output+out_offset + 12); +} + +__kernel void gemm_b4_c2_buf(GLOBAL_SIZE_DIM2 + __global const FLOAT* input, +#if (defined USE_LOW_BIT_WEIGHT_INT8) + __global const char *weight, +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + __global const uchar *weight, +#endif + __global const float *dequantScaleOffset, + __global const FLOAT *bias, + __global FLOAT* output, + __private const int dstChannelC4, + __private const int srcChannelC4, + __private const int blockNum, + __private const int blockDim) { + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + + UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_c_idx = x; + const int out_b_idx = y << 2; + + COMPUTE_FLOAT2 bias0 = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, bias)); + COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0.s0; + COMPUTE_FLOAT4 out1 = (COMPUTE_FLOAT4)bias0.s1; + + int input_offset = out_b_idx * srcChannelC4 * 4; + int out_offset = (out_b_idx * dstChannelC4 + out_c_idx * 2) * 4; + +#if (defined USE_LOW_BIT_WEIGHT_INT4) + int weight_offset = out_c_idx * 2 * 8; + int weight_oc_offset = dstChannelC4 * 32; +#else + int weight_offset = out_c_idx * 2 * 16; + int weight_oc_offset = dstChannelC4 * 64; +#endif + + const int loop = (blockDim + 15) / 16; +#ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*16; +#else + const int loop_end = loop; +#endif + + for (int i = 0; i < blockNum; i++){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT4 ScaleOffset = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, dequantScaleOffset + kindex)); + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0, weights1; +#if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt4 = vload16(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } +#endif + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights1_ptr[i], out1); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k16 = k << 4; + + COMPUTE_FLOAT16 weights0, weights1; +#if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt4 = vload16(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } +#endif + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + for (int i = 0; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights1_ptr[i], out1); + } + } +#endif + } + +#ifdef RELU + out = fmax(out, (COMPUTE_FLOAT4)0); + out1 = fmax(out1, (COMPUTE_FLOAT4)0); +#endif + +#ifdef RELU6 + out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out1 = clamp(out1, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); +#endif + + vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); + vstore4(CONVERT_FLOAT4(out1), 0, output+out_offset+4); +} + +__kernel void gemm_b4_c1_buf(GLOBAL_SIZE_DIM2 + __global const FLOAT* input, +#if (defined USE_LOW_BIT_WEIGHT_INT8) + __global const char *weight, +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + __global const uchar *weight, +#endif + __global const float *dequantScaleOffset, + __global const FLOAT *bias, + __global FLOAT* output, + __private const int dstChannelC4, + __private const int srcChannelC4, + __private const int blockNum, + __private const int blockDim) { + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + + UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_c_idx = x; + const int out_b_idx = y << 2; + + COMPUTE_FLOAT bias0 = bias[out_c_idx]; + COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0; + + int input_offset = out_b_idx * srcChannelC4 * 4; + int out_offset = (out_b_idx * dstChannelC4 + out_c_idx) * 4; + +#if (defined USE_LOW_BIT_WEIGHT_INT4) + int weight_offset = out_c_idx * 8; + int weight_oc_offset = dstChannelC4 * 32; +#else + int weight_offset = out_c_idx * 16; + int weight_oc_offset = dstChannelC4 * 64; +#endif + + const int loop = (blockDim + 15) / 16; +#ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*16; +#else + const int loop_end = loop; +#endif + + for (int i = 0; i < blockNum; i++){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT2 ScaleOffset = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantScaleOffset + kindex)); + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k16 = k << 4; + COMPUTE_FLOAT16 weights; +#if (defined USE_LOW_BIT_WEIGHT_INT8) + weights = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights = 0; + UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); + weights = CONVERT_COMPUTE_FLOAT16(charWeights) * ScaleOffset.s0 + ScaleOffset.s1; + } +#endif + COMPUTE_FLOAT *weights_ptr = (COMPUTE_FLOAT *)&weights; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights_ptr[i], out); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k16 = k << 4; + COMPUTE_FLOAT16 weights; +#if (defined USE_LOW_BIT_WEIGHT_INT8) + weights = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights = 0; + UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); + weights = CONVERT_COMPUTE_FLOAT16(charWeights) * ScaleOffset.s0 + ScaleOffset.s1; + } +#endif + COMPUTE_FLOAT *weights_ptr = (COMPUTE_FLOAT *)&weights; + for (int i = 0; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights_ptr[i], out); + } + } +#endif + } + +#ifdef RELU + out = fmax(out, (COMPUTE_FLOAT4)0); +#endif + +#ifdef RELU6 + out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); +#endif + vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); +} +__kernel void gemm_b4_c2_image(GLOBAL_SIZE_DIM2 + __global const FLOAT* input, + __read_only image2d_t weight, + __global const float *dequantScaleOffset, + __global const FLOAT *bias, + __global FLOAT* output, + __private const int dstChannelC4, + __private const int srcChannelC4, + __private const int blockNum, + __private const int blockDim) { + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_c_idx = x << 1; + const int out_b_idx = y << 2; + + COMPUTE_FLOAT2 bias0 = CONVERT_COMPUTE_FLOAT2(vload2(0, bias + out_c_idx)); + COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0.s0; + COMPUTE_FLOAT4 out1 = (COMPUTE_FLOAT4)bias0.s1; + + int input_offset = out_b_idx * srcChannelC4 * 4; + int out_offset = (out_b_idx * dstChannelC4 + out_c_idx) * 4; + +#if (defined USE_LOW_BIT_WEIGHT_INT8) + const int loop = (blockDim + 15) / 16; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*16; + #else + const int loop_end = loop; + #endif +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + const int loop = (blockDim + 31) / 32; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*32; + #else + const int loop_end = loop; + #endif +#endif + + for (int i = 0; i < blockNum; i++){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT4 ScaleOffset = CONVERT_COMPUTE_FLOAT4(vload4(0, dequantScaleOffset + out_c_idx * 2 + kindex)); +#if (defined USE_LOW_BIT_WEIGHT_INT8) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + COMPUTE_FLOAT16 weights1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k)))) * ScaleOffset.s2 + ScaleOffset.s3; + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights1_ptr[i], out1); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + COMPUTE_FLOAT16 weights1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k)))) * ScaleOffset.s2 + ScaleOffset.s3; + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + #pragma unroll + for (int i = 0; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights1_ptr[i], out1); + } + } +#endif +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k32 = k << 5; + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + COMPUTE_FLOAT *weights2_ptr = (COMPUTE_FLOAT *)&weights2; + COMPUTE_FLOAT *weights3_ptr = (COMPUTE_FLOAT *)&weights3; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights2_ptr[i], out1); + } + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i + 16) * 4)); + out = mad(in, weights1_ptr[i], out); + out1 = mad(in, weights3_ptr[i], out1); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k32 = k << 5; + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + COMPUTE_FLOAT *weights2_ptr = (COMPUTE_FLOAT *)&weights2; + COMPUTE_FLOAT *weights3_ptr = (COMPUTE_FLOAT *)&weights3; + for (int i = 0; i < min(16, remain); ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + out1 = mad(in, weights2_ptr[i], out1); + } + for (int i = 16; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); + out = mad(in, weights1_ptr[i - 16], out); + out1 = mad(in, weights3_ptr[i - 16], out1); + } + } +#endif +#endif //USE_LOW_BIT_WEIGHT_INT4 + } + +#ifdef RELU + out = fmax(out, (COMPUTE_FLOAT4)0); + out1 = fmax(out1, (COMPUTE_FLOAT4)0); +#endif +#ifdef RELU6 + out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); + out1 = clamp(out1, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); +#endif + vstore4(CONVERT_FLOAT4(out), 0, output + out_offset); + vstore4(CONVERT_FLOAT4(out1), 0, output + out_offset + 4); +} +__kernel void gemm_b4_c1_image(GLOBAL_SIZE_DIM2 + __global const FLOAT* input, + __read_only image2d_t weight, + __global const float *dequantScaleOffset, + __global const FLOAT *bias, + __global FLOAT* output, + __private const int dstChannelC4, + __private const int srcChannelC4, + __private const int blockNum, + __private const int blockDim) { + const int x = get_global_id(0); //c + const int y = get_global_id(1); //b + UNIFORM_BOUNDRY_CHECK(x, y); + + const int out_c_idx = x; + const int out_b_idx = y << 2; + + COMPUTE_FLOAT bias0 = bias[out_c_idx]; + COMPUTE_FLOAT4 out = (COMPUTE_FLOAT4)bias0; + + int input_offset = out_b_idx * srcChannelC4 * 4; + int out_offset = (out_b_idx * dstChannelC4 + out_c_idx) * 4; + +#if (defined USE_LOW_BIT_WEIGHT_INT8) + const int loop = (blockDim + 15) / 16; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*16; + #else + const int loop_end = loop; + #endif +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + const int loop = (blockDim + 31) / 32; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + const int remain = blockDim - loop_end*32; + #else + const int loop_end = loop; + #endif +#endif + + for (int i = 0; i < blockNum; ++i){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT2 ScaleOffset = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantScaleOffset + kindex)); +#if (defined USE_LOW_BIT_WEIGHT_INT8) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k16 = k << 4; + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + #pragma unroll + for (int i = 0; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k16 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + } + } +#endif +#elif (defined USE_LOW_BIT_WEIGHT_INT4) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + int k32 = k << 5; + COMPUTE_FLOAT16 weights0, weights1; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + } + #pragma unroll + for (int i = 0; i < 16; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i + 16) * 4)); + out = mad(in, weights1_ptr[i], out); + } + } +#ifdef INPUT_CHANNEL_LEAVE + { + int k = i * loop + loop_end; + int k32 = k << 5; + COMPUTE_FLOAT16 weights0, weights1; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + COMPUTE_FLOAT *weights0_ptr = (COMPUTE_FLOAT *)&weights0; + COMPUTE_FLOAT *weights1_ptr = (COMPUTE_FLOAT *)&weights1; + for (int i = 0; i < min(16, remain); ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); + out = mad(in, weights0_ptr[i], out); + } + for (int i = 16; i < remain; ++i){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k32 + i) * 4)); + out = mad(in, weights1_ptr[i - 16], out); + } + } +#endif +#endif //USE_LOW_BIT_WEIGHT_INT4 + } + +#ifdef RELU + out = fmax(out, (COMPUTE_FLOAT4)0); +#endif +#ifdef RELU6 + out = clamp(out, (COMPUTE_FLOAT4)0, (COMPUTE_FLOAT4)6); +#endif + vstore4(CONVERT_FLOAT4(out), 0, output+out_offset); +} + diff --git a/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl b/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl index 9c762a8bf..7b4433111 100644 --- a/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl +++ b/source/backend/opencl/execution/cl/gemv_conv1x1_buf.cl @@ -26,6 +26,18 @@ c += dot(a.s89ab, b.s89ab); \ c += dot(a.scdef, b.scdef); +#ifdef INPUT_CHANNEL_LEAVE + #define PADZEROS(k, channel, data) {\ + COMPUTE_FLOAT* ptr = (COMPUTE_FLOAT*)&data; \ + int remain = k + 15 - channel; \ + for(int r = remain; r >= 0; r--){ \ + ptr[15 - remain] = 0; \ + } \ + } +#else + #define PADZEROS(k, channel, data) +#endif + __constant sampler_t SAMPLER = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST; __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 @@ -35,15 +47,17 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, __private const int dstChannelC4, __private const int srcChannelC4, + __private const int srcChannel, __private const int batch, __private const int height, - __private const int width) { + __private const int width, + __private const int blockNum, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -59,11 +73,9 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 const int out_h_idx = out_b_h_idx % height; COMPUTE_FLOAT4 bias0 = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, bias)); - COMPUTE_FLOAT sum = 0; - COMPUTE_FLOAT4 out = 0; + COMPUTE_FLOAT4 out = bias0; #ifdef BACTH_BLOCK4 - COMPUTE_FLOAT sum1 = 0, sum2 = 0, sum3 = 0; - COMPUTE_FLOAT4 out1 = 0, out2 = 0, out3 = 0; + COMPUTE_FLOAT4 out1 = bias0, out2 = bias0, out3 = bias0; int input_offset1 = (((out_b_idx + 1) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset2 = (((out_b_idx + 2) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset3 = (((out_b_idx + 3) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; @@ -74,9 +86,7 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 int input_offset = ((out_b_idx * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int out_offset = (((out_b_idx * dstChannelC4 + out_c_idx) * height + out_h_idx) * width + out_w_idx) * 4; -#ifndef WIDTH_HEIGHT_1 int wh = width * height * 4; -#endif #if (defined USE_LOW_BIT_WEIGHT_INT4) int weight_offset = out_c_idx * 4 * 8; int weight_oc_offset = dstChannelC4 * 32; @@ -84,187 +94,187 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 int weight_offset = out_c_idx * 4 * 16; int weight_oc_offset = dstChannelC4 * 64; #endif - - const COMPUTE_FLOAT4 Scale = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, dequantScale)); - const COMPUTE_FLOAT4 Offset = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, dequantOffset)); - + + const int loop = (blockDim + 15) / 16; #ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC16 = (srcChannelC4 + 3) >> 2; - for (int k = 0; k < srcChannelC16 - 1; ++k) { + const int loop_end = max(loop - 1, 0); #else - for (int k = 0; k < srcChannelC4/4; ++k) { + const int loop_end = loop; #endif -#ifndef WIDTH_HEIGHT_1 - int k4 = k << 2; -#endif - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; -#if (defined USE_LOW_BIT_WEIGHT_INT8) - weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); - weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)); - weights2 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 32)); - weights3 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 48)); -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - { - uchar16 charWeightsInt40 = vload16(0, weight + weight_offset + k * weight_oc_offset); - uchar16 charWeightsInt41 = vload16(0, weight + weight_offset + k * weight_oc_offset + 16); + + for (int i = 0; i < blockNum; ++i){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT8 ScaleOffset = CONVERT_COMPUTE_FLOAT8(vload8(out_c_idx, dequantScaleOffset + kindex)); + for (int j = 0; j < loop_end; ++j) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k4 = k << 2; + #endif + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; + #if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; + weights2 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 32)) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 48)) * ScaleOffset.s6 + ScaleOffset.s7; + #elif (defined USE_LOW_BIT_WEIGHT_INT4) { - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1); + uchar16 charWeightsInt40 = vload16(0, weight + weight_offset + k * weight_oc_offset); + uchar16 charWeightsInt41 = vload16(0, weight + weight_offset + k * weight_oc_offset + 16); + { + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; + } } + #endif + { + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out.s0); + DOT16X16(in, weights1, out.s1); + DOT16X16(in, weights2, out.s2); + DOT16X16(in, weights3, out.s3); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset1)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out1.s0); + DOT16X16(in, weights1, out1.s1); + DOT16X16(in, weights2, out1.s2); + DOT16X16(in, weights3, out1.s3); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset2)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out2.s0); + DOT16X16(in, weights1, out2.s1); + DOT16X16(in, weights2, out2.s2); + DOT16X16(in, weights3, out2.s3); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset3)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out3.s0); + DOT16X16(in, weights1, out3.s1); + DOT16X16(in, weights2, out3.s2); + DOT16X16(in, weights3, out3.s3); + } + #endif } -#endif - { - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); -#endif - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out.s1); - DOT16X16(in, weights2, out.s2); - DOT16X16(in, weights3, out.s3); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset1)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); -#endif - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1.s0); - DOT16X16(in, weights1, out1.s1); - DOT16X16(in, weights2, out1.s2); - DOT16X16(in, weights3, out1.s3); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset2)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); -#endif - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2.s0); - DOT16X16(in, weights1, out2.s1); - DOT16X16(in, weights2, out2.s2); - DOT16X16(in, weights3, out2.s3); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset3)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); -#endif - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3.s0); - DOT16X16(in, weights1, out3.s1); - DOT16X16(in, weights2, out3.s2); - DOT16X16(in, weights3, out3.s3); - } -#endif - } -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC16 - 1; - int k4 = k * 4; - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; -#if (defined USE_LOW_BIT_WEIGHT_INT8) - weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); - weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)); - weights2 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 32)); - weights3 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 48)); -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - { - uchar16 charWeightsInt40 = vload16(0, weight + weight_offset + k * weight_oc_offset); - uchar16 charWeightsInt41 = vload16(0, weight + weight_offset + k * weight_oc_offset + 16); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); - weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1); - } -#endif + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out.s1); - DOT16X16(in, weights2, out.s2); - DOT16X16(in, weights3, out.s3); - } - -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1.s0); - DOT16X16(in, weights1, out1.s1); - DOT16X16(in, weights2, out1.s2); - DOT16X16(in, weights3, out1.s3); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2.s0); - DOT16X16(in, weights1, out2.s1); - DOT16X16(in, weights2, out2.s2); - DOT16X16(in, weights3, out2.s3); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3.s0); - DOT16X16(in, weights1, out3.s1); - DOT16X16(in, weights2, out3.s2); - DOT16X16(in, weights3, out3.s3); + int k = i * loop + loop_end; + int k4 = k << 2; + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; + #if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; + weights2 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 32)) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 48)) * ScaleOffset.s6 + ScaleOffset.s7; + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt40 = vload16(0, weight + weight_offset + k * weight_oc_offset); + uchar16 charWeightsInt41 = vload16(0, weight + weight_offset + k * weight_oc_offset + 16); + { + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt40); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt41); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s4 + ScaleOffset.s5; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s6 + ScaleOffset.s7; + } + } + #endif + PADZEROS(k, srcChannel, weights0); + PADZEROS(k, srcChannel, weights1); + PADZEROS(k, srcChannel, weights2); + PADZEROS(k, srcChannel, weights3); + { + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out.s0); + DOT16X16(in, weights1, out.s1); + DOT16X16(in, weights2, out.s2); + DOT16X16(in, weights3, out.s3); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out1.s0); + DOT16X16(in, weights1, out1.s1); + DOT16X16(in, weights2, out1.s2); + DOT16X16(in, weights3, out1.s3); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out2.s0); + DOT16X16(in, weights1, out2.s1); + DOT16X16(in, weights2, out2.s2); + DOT16X16(in, weights3, out2.s3); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out3.s0); + DOT16X16(in, weights1, out3.s1); + DOT16X16(in, weights2, out3.s2); + DOT16X16(in, weights3, out3.s3); + } + #endif } -#endif + #endif } -#endif - out = bias0 + mad(out, Scale, sum * Offset); #ifdef RELU out = fmax(out, (COMPUTE_FLOAT4)0); #endif @@ -277,7 +287,6 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 #ifdef BACTH_BLOCK4 if(isValidBatch1){ out_offset += dstChannelC4 * height * width * 4; - out1 = bias0 + mad(out1, Scale, sum1 * Offset); #ifdef RELU out1 = fmax(out1, (COMPUTE_FLOAT4)0); #endif @@ -290,7 +299,6 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 } if(isValidBatch2){ out_offset += dstChannelC4 * height * width * 4; - out2 = bias0 + mad(out2, Scale, sum2 * Offset); #ifdef RELU out2 = fmax(out2, (COMPUTE_FLOAT4)0); #endif @@ -303,7 +311,6 @@ __kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2 } if(isValidBatch3){ out_offset += dstChannelC4 * height * width * 4; - out3 = bias0 + mad(out3, Scale, sum3 * Offset); #ifdef RELU out3 = fmax(out3, (COMPUTE_FLOAT4)0); #endif @@ -324,15 +331,17 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, __private const int dstChannelC4, __private const int srcChannelC4, + __private const int srcChannel, __private const int batch, __private const int height, - __private const int width) { + __private const int width, + __private const int blockNum, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -348,11 +357,9 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 const int out_h_idx = out_b_h_idx % height; COMPUTE_FLOAT2 bias0 = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, bias)); - COMPUTE_FLOAT sum = 0; - COMPUTE_FLOAT2 out = 0; + COMPUTE_FLOAT2 out = bias0; #ifdef BACTH_BLOCK4 - COMPUTE_FLOAT sum1 = 0, sum2 = 0, sum3 = 0; - COMPUTE_FLOAT2 out1 = 0, out2 = 0, out3 = 0; + COMPUTE_FLOAT2 out1 = bias0, out2 = bias0, out3 = bias0; int input_offset1 = (((out_b_idx + 1) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset2 = (((out_b_idx + 2) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset3 = (((out_b_idx + 3) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; @@ -362,9 +369,7 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 #endif int input_offset = ((out_b_idx * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int out_offset = (((out_b_idx * dstChannelC4 + (out_c_idx * 2) / 4) * height + out_h_idx) * width + out_w_idx) * 4 + ((out_c_idx * 2)%4); -#ifndef WIDTH_HEIGHT_1 int wh = width * height * 4; -#endif #if (defined USE_LOW_BIT_WEIGHT_INT4) int weight_offset = out_c_idx * 2 * 8; int weight_oc_offset = dstChannelC4 * 32; @@ -373,156 +378,152 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 int weight_oc_offset = dstChannelC4 * 64; #endif - const COMPUTE_FLOAT2 Scale = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantScale)); - const COMPUTE_FLOAT2 Offset = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantOffset)); - + const int loop = (blockDim + 15) / 16; #ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC16 = (srcChannelC4 + 3) >> 2; - for (int k = 0; k < srcChannelC16 - 1; ++k) { + const int loop_end = max(loop - 1, 0); #else - for (int k = 0; k < srcChannelC4/4; ++k) { -#endif -#ifndef WIDTH_HEIGHT_1 - int k4 = k << 2; + const int loop_end = loop; #endif - COMPUTE_FLOAT16 weights0, weights1; -#if (defined USE_LOW_BIT_WEIGHT_INT8) - weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); - weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)); -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - { - uchar16 charWeightsInt4 = vload16(0, weight + weight_offset + k * weight_oc_offset); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); - } -#endif - { - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); -#endif - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out.s1); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset1)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); -#endif - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1.s0); - DOT16X16(in, weights1, out1.s1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset2)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); -#endif - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2.s0); - DOT16X16(in, weights1, out2.s1); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset3)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); -#endif - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3.s0); - DOT16X16(in, weights1, out3.s1); - } -#endif - } -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC16 - 1; - int k4 = k * 4; - COMPUTE_FLOAT16 weights0, weights1; -#if (defined USE_LOW_BIT_WEIGHT_INT8) - weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); - weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)); -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - { - uchar16 charWeightsInt4 = vload16(0, weight + weight_offset + k * weight_oc_offset); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); + for (int i = 0; i < blockNum; ++i){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT4 ScaleOffset = CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx, dequantScaleOffset + kindex)); + for (int j = 0; j < loop_end; ++j) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k4 = k << 2; + #endif + COMPUTE_FLOAT16 weights0, weights1; + #if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt4 = vload16(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } + #endif + { + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out.s0); + DOT16X16(in, weights1, out.s1); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset1)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out1.s0); + DOT16X16(in, weights1, out1.s1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset2)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out2.s0); + DOT16X16(in, weights1, out2.s1); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset3)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out3.s0); + DOT16X16(in, weights1, out3.s1); + } + #endif } -#endif + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out.s1); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1.s0); - DOT16X16(in, weights1, out1.s1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2.s0); - DOT16X16(in, weights1, out2.s1); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3.s0); - DOT16X16(in, weights1, out3.s1); + int k = i * loop + loop_end; + int k4 = k << 2; + COMPUTE_FLOAT16 weights0, weights1; + #if (defined USE_LOW_BIT_WEIGHT_INT8) + weights0 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset + 16)) * ScaleOffset.s2 + ScaleOffset.s3; + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar16 charWeightsInt4 = vload16(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } + #endif + PADZEROS(k, srcChannel, weights0); + PADZEROS(k, srcChannel, weights1); + { + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out.s0); + DOT16X16(in, weights1, out.s1); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out1.s0); + DOT16X16(in, weights1, out1.s1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out2.s0); + DOT16X16(in, weights1, out2.s1); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out3.s0); + DOT16X16(in, weights1, out3.s1); + } + #endif } -#endif + #endif } -#endif - out = bias0 + mad(out, Scale, sum * Offset); #ifdef RELU out = fmax(out, (COMPUTE_FLOAT2)0); #endif @@ -535,7 +536,6 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 #ifdef BACTH_BLOCK4 if(isValidBatch1){ out_offset += dstChannelC4 * height * width * 4; - out1 = bias0 + mad(out1, Scale, sum1 * Offset); #ifdef RELU out1 = fmax(out1, (COMPUTE_FLOAT2)0); #endif @@ -548,7 +548,6 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 } if(isValidBatch2){ out_offset += dstChannelC4 * height * width * 4; - out2 = bias0 + mad(out2, Scale, sum2 * Offset); #ifdef RELU out2 = fmax(out2, (COMPUTE_FLOAT2)0); #endif @@ -561,7 +560,6 @@ __kernel void gemm_conv_c2_buf(GLOBAL_SIZE_DIM2 } if(isValidBatch3){ out_offset += dstChannelC4 * height * width * 4; - out3 = bias0 + mad(out3, Scale, sum3 * Offset); #ifdef RELU out3 = fmax(out3, (COMPUTE_FLOAT2)0); #endif @@ -582,15 +580,17 @@ __kernel void gemm_conv_c1_buf(GLOBAL_SIZE_DIM2 #elif (defined USE_LOW_BIT_WEIGHT_INT4) __global const uchar *weight, #endif - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, __private const int dstChannelC4, __private const int srcChannelC4, + __private const int srcChannel, __private const int batch, __private const int height, - __private const int width) { + __private const int width, + __private const int blockNum, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h @@ -606,12 +606,10 @@ __kernel void gemm_conv_c1_buf(GLOBAL_SIZE_DIM2 const int out_h_idx = out_b_h_idx % height; COMPUTE_FLOAT bias0 = bias[out_c_idx]; - COMPUTE_FLOAT sum = 0; - COMPUTE_FLOAT out = 0; + COMPUTE_FLOAT out = bias0; #ifdef BACTH_BLOCK4 - COMPUTE_FLOAT sum1 = 0, sum2 = 0, sum3 = 0; - COMPUTE_FLOAT out1 = 0, out2 = 0, out3 = 0; + COMPUTE_FLOAT out1 = bias0, out2 = bias0, out3 = bias0; int input_offset1 = (((out_b_idx + 1) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset2 = (((out_b_idx + 2) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset3 = (((out_b_idx + 3) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; @@ -622,9 +620,7 @@ __kernel void gemm_conv_c1_buf(GLOBAL_SIZE_DIM2 int input_offset = ((out_b_idx * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int out_offset = (((out_b_idx * dstChannelC4 + out_c_idx/4) * height + out_h_idx) * width + out_w_idx) * 4 + (out_c_idx%4); -#ifndef WIDTH_HEIGHT_1 int wh = width * height * 4; -#endif #if (defined USE_LOW_BIT_WEIGHT_INT4) int weight_offset = out_c_idx * 8; int weight_oc_offset = dstChannelC4 * 32; @@ -632,185 +628,179 @@ __kernel void gemm_conv_c1_buf(GLOBAL_SIZE_DIM2 int weight_offset = out_c_idx * 16; int weight_oc_offset = dstChannelC4 * 64; #endif - - const COMPUTE_FLOAT Scale = dequantScale[out_c_idx]; - const COMPUTE_FLOAT Offset = dequantOffset[out_c_idx]; + + const int loop = (blockDim + 15) / 16; #ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC16 = (srcChannelC4 + 3) >> 2; - for (int k = 0; k < srcChannelC16 - 1; ++k) { -#else - for (int k = 0; k < srcChannelC4/4; ++k) { -#endif -#ifndef WIDTH_HEIGHT_1 - int k4 = k << 2; -#endif - COMPUTE_FLOAT16 weights; -#if (defined USE_LOW_BIT_WEIGHT_INT8) - weights = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - { - uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); - char16 charWeights = 0; - UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); - weights = CONVERT_COMPUTE_FLOAT16(charWeights); - } -#endif - { - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); -#endif - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset1)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); -#endif - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset2)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); -#endif - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out2); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset3)); + const int loop_end = max(loop - 1, 0); #else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); + const int loop_end = loop; #endif - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out3); - } -#endif - } -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC16 - 1; - int k4 = k * 4; - COMPUTE_FLOAT16 weights; -#if (defined USE_LOW_BIT_WEIGHT_INT8) - weights = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)); -#elif (defined USE_LOW_BIT_WEIGHT_INT4) - { - uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); - char16 charWeights = 0; - UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); - weights = CONVERT_COMPUTE_FLOAT16(charWeights); + + for (int i = 0; i < blockNum; ++i){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT2 ScaleOffset = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantScaleOffset + kindex)); + for (int j = 0; j < loop_end; ++j) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k4 = k << 2; + #endif + COMPUTE_FLOAT16 weights; + #if (defined USE_LOW_BIT_WEIGHT_INT8) + weights = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights = 0; + UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); + weights = CONVERT_COMPUTE_FLOAT16(charWeights) * ScaleOffset.s0 + ScaleOffset.s1; + } + #endif + { + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights, out); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset1)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights, out1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset2)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights, out2); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(k, input + input_offset3)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights, out3); + } + #endif } -#endif + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out2); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights, out3); + int k = i * loop + loop_end; + int k4 = k << 2; + COMPUTE_FLOAT16 weights; + #if (defined USE_LOW_BIT_WEIGHT_INT8) + weights = CONVERT_COMPUTE_FLOAT16(vload16(0, weight + weight_offset + k * weight_oc_offset)) * ScaleOffset.s0 + ScaleOffset.s1; + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + { + uchar8 charWeightsInt4 = vload8(0, weight + weight_offset + k * weight_oc_offset); + char16 charWeights = 0; + UCHAR8_TO_CHAR16(charWeights, charWeightsInt4); + weights = CONVERT_COMPUTE_FLOAT16(charWeights) * ScaleOffset.s0 + ScaleOffset.s1; + } + #endif + PADZEROS(k, srcChannel, weights); + { + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights, out); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights, out1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights, out2); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights, out3); + } + #endif } -#endif + #endif } -#endif - out = bias0 + mad(out, Scale, sum * Offset); #ifdef RELU - out = fmax(out, 0); + out = fmax(out, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out = clamp(out, 0, 6); + out = clamp(out, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out; #ifdef BACTH_BLOCK4 if(isValidBatch1){ out_offset += dstChannelC4 * height * width * 4; - out1 = bias0 + mad(out1, Scale, sum1 * Offset); #ifdef RELU - out1 = fmax(out1, 0); + out1 = fmax(out1, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out1 = clamp(out1, 0, 6); + out1 = clamp(out1, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out1; } if(isValidBatch2){ out_offset += dstChannelC4 * height * width * 4; - out2 = bias0 + mad(out2, Scale, sum2 * Offset); #ifdef RELU - out2 = fmax(out2, 0); + out2 = fmax(out2, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out2 = clamp(out2, 0, 6); + out2 = clamp(out2, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out2; } if(isValidBatch3){ out_offset += dstChannelC4 * height * width * 4; - out3 = bias0 + mad(out3, Scale, sum3 * Offset); #ifdef RELU - out3 = fmax(out3, 0); + out3 = fmax(out3, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out3 = clamp(out3, 0, 6); + out3 = clamp(out3, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out3; @@ -820,15 +810,17 @@ __kernel void gemm_conv_c1_buf(GLOBAL_SIZE_DIM2 __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 __global const FLOAT* input, __read_only image2d_t weight, - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, __private const int dstChannelC4, __private const int srcChannelC4, + __private const int srcChannel, __private const int batch, __private const int height, - __private const int width) { + __private const int width, + __private const int blockNum, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h UNIFORM_BOUNDRY_CHECK(out_c_w_idx, out_b_h_idx); @@ -843,12 +835,10 @@ __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 const int out_h_idx = out_b_h_idx % height; COMPUTE_FLOAT2 bias0 = CONVERT_COMPUTE_FLOAT2(vload2(0, bias + out_c_idx)); - COMPUTE_FLOAT2 out = 0; - COMPUTE_FLOAT sum = 0; + COMPUTE_FLOAT2 out = bias0; #ifdef BACTH_BLOCK4 - COMPUTE_FLOAT sum1 = 0, sum2 = 0, sum3 = 0; - COMPUTE_FLOAT2 out1 = 0, out2 = 0, out3 = 0; + COMPUTE_FLOAT2 out1 = bias0, out2 = bias0, out3 = bias0; int input_offset1 = (((out_b_idx + 1) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset2 = (((out_b_idx + 2) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset3 = (((out_b_idx + 3) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; @@ -859,357 +849,349 @@ __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 int input_offset = ((out_b_idx * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int out_offset = (((out_b_idx * dstChannelC4 + out_c_idx/4) * height + out_h_idx) * width + out_w_idx) * 4 + (out_c_idx % 4); -#ifndef WIDTH_HEIGHT_1 int wh = width * height * 4; -#endif - - const COMPUTE_FLOAT2 Scale = CONVERT_COMPUTE_FLOAT2(vload2(0, dequantScale + out_c_idx)); - const COMPUTE_FLOAT2 Offset = CONVERT_COMPUTE_FLOAT2(vload2(0, dequantOffset + out_c_idx)); #if (defined USE_LOW_BIT_WEIGHT_INT8) -#ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC16 = (srcChannelC4 + 3) >> 2; - for (int k = 0; k < srcChannelC16-1; k++) { -#else - for (int k = 0; k < srcChannelC4/4; k++) { -#endif -#ifndef WIDTH_HEIGHT_1 - int k4 = k * 4; -#endif - COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k)))); - COMPUTE_FLOAT16 weights1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagef(weight, SAMPLER, (int2)(out_c_idx + 1, k)))); - { - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); -#endif - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out.s1); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); -#endif - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1.s0); - DOT16X16(in, weights1, out1.s1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); -#endif - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2.s0); - DOT16X16(in, weights1, out2.s1); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); -#endif - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3.s0); - DOT16X16(in, weights1, out3.s1); - } -#endif - } -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC16 - 1; - int k4 = k * 4; - COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k)))); - COMPUTE_FLOAT16 weights1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagef(weight, SAMPLER, (int2)(out_c_idx + 1, k)))); - { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out.s0); - DOT16X16(in, weights1, out.s1); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1.s0); - DOT16X16(in, weights1, out1.s1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2.s0); - DOT16X16(in, weights1, out2.s1); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3.s0); - DOT16X16(in, weights1, out3.s1); - } -#endif - } -#endif + const int loop = (blockDim + 15) / 16; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + #else + const int loop_end = loop; + #endif #elif (defined USE_LOW_BIT_WEIGHT_INT4) -#ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC32 = (srcChannelC4 + 7) >> 3; - for (int k = 0; k < srcChannelC32-1; k++) { -#else - for (int k = 0; k < srcChannelC4/8; k++) { -#endif -#ifndef WIDTH_HEIGHT_1 - int k8 = k * 8; + const int loop = (blockDim + 31) / 32; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + #else + const int loop_end = loop; + #endif #endif - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; - { - uchar16 charWeightsInt4 = as_uchar16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k))); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); - } - { - uchar16 charWeightsInt4 = as_uchar16(read_imagef(weight, SAMPLER, (int2)(out_c_idx + 1, k))); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1); + + for (int i = 0; i < blockNum; ++i){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT4 ScaleOffset = CONVERT_COMPUTE_FLOAT4(vload4(0, dequantScaleOffset + out_c_idx * 2 + kindex)); + #if (defined USE_LOW_BIT_WEIGHT_INT8) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k4 = k << 2; + #endif + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + COMPUTE_FLOAT16 weights1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k)))) * ScaleOffset.s2 + ScaleOffset.s3; + { + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out.s0); + DOT16X16(in, weights1, out.s1); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out1.s0); + DOT16X16(in, weights1, out1.s1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out2.s0); + DOT16X16(in, weights1, out2.s1); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out3.s0); + DOT16X16(in, weights1, out3.s1); + } + #endif } + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 3) * wh)); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 7) * wh)); + int k = i * loop + loop_end; + int k4 = k << 2; + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + COMPUTE_FLOAT16 weights1 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k)))) * ScaleOffset.s2 + ScaleOffset.s3; + PADZEROS(k, srcChannel, weights0); + PADZEROS(k, srcChannel, weights1); + { + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out.s0); + DOT16X16(in, weights1, out.s1); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out1.s0); + DOT16X16(in, weights1, out1.s1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out2.s0); + DOT16X16(in, weights1, out2.s1); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out3.s0); + DOT16X16(in, weights1, out3.s1); + } + #endif + } + #endif + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k8 = k << 3; + #endif + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } + { + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 3) * wh)); -#endif - sum += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out.s0); - DOT16X16(in1, weights1, out.s0); - DOT16X16(in0, weights2, out.s1); - DOT16X16(in1, weights3, out.s1); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 3) * wh)); + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 7) * wh)); + #endif + + DOT16X16(in0, weights0, out.s0); + DOT16X16(in1, weights1, out.s0); + DOT16X16(in0, weights2, out.s1); + DOT16X16(in1, weights3, out.s1); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 3) * wh)); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 7) * wh)); -#endif - sum1 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum1 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out1.s0); - DOT16X16(in1, weights1, out1.s0); - DOT16X16(in0, weights2, out1.s1); - DOT16X16(in1, weights3, out1.s1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 3) * wh)); + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out1.s0); + DOT16X16(in1, weights1, out1.s0); + DOT16X16(in0, weights2, out1.s1); + DOT16X16(in1, weights3, out1.s1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 3) * wh)); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 7) * wh)); -#endif - sum2 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum2 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out2.s0); - DOT16X16(in1, weights1, out2.s0); - DOT16X16(in0, weights2, out2.s1); - DOT16X16(in1, weights3, out2.s1); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 3) * wh)); + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out2.s0); + DOT16X16(in1, weights1, out2.s0); + DOT16X16(in0, weights2, out2.s1); + DOT16X16(in1, weights3, out2.s1); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 3) * wh)); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 7) * wh)); -#endif - sum3 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum3 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out3.s0); - DOT16X16(in1, weights1, out3.s0); - DOT16X16(in0, weights2, out3.s1); - DOT16X16(in1, weights3, out3.s1); - } -#endif - } -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC32 - 1; - int k8 = k * 8; - COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; - { - uchar16 charWeightsInt4 = as_uchar16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k))); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); - } - { - uchar16 charWeightsInt4 = as_uchar16(read_imagef(weight, SAMPLER, (int2)(out_c_idx + 1, k))); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1); + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out3.s0); + DOT16X16(in1, weights1, out3.s0); + DOT16X16(in0, weights2, out3.s1); + DOT16X16(in1, weights3, out3.s1); + } + #endif } + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 7) * wh) : (FLOAT4)0); - sum += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out.s0); - DOT16X16(in1, weights1, out.s0); - DOT16X16(in0, weights2, out.s1); - DOT16X16(in1, weights3, out.s1); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < vload4(0, input + input_offset1 + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < vload4(0, input + input_offset1 + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < vload4(0, input + input_offset1 + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 7) * wh) : (FLOAT4)0); - sum1 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum1 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out1.s0); - DOT16X16(in1, weights1, out1.s0); - DOT16X16(in0, weights2, out1.s1); - DOT16X16(in1, weights3, out1.s1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < vload4(0, input + input_offset2 + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < vload4(0, input + input_offset2 + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < vload4(0, input + input_offset2 + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 7) * wh) : (FLOAT4)0); - sum2 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum2 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out2.s0); - DOT16X16(in1, weights1, out2.s0); - DOT16X16(in0, weights2, out2.s1); - DOT16X16(in1, weights3, out2.s1); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < vload4(0, input + input_offset3 + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < vload4(0, input + input_offset3 + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < vload4(0, input + input_offset3 + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 7) * wh) : (FLOAT4)0); - sum3 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum3 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out3.s0); - DOT16X16(in1, weights1, out3.s0); - DOT16X16(in0, weights2, out3.s1); - DOT16X16(in1, weights3, out3.s1); + int k = i * loop + loop_end; + int k8 = k << 3; + COMPUTE_FLOAT16 weights0, weights1, weights2, weights3; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx + 1, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights2 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s2 + ScaleOffset.s3; + weights3 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s2 + ScaleOffset.s3; + } + PADZEROS(k, srcChannel, weights0); + PADZEROS(k + 15, srcChannel, weights1); + PADZEROS(k, srcChannel, weights2); + PADZEROS(k + 15, srcChannel, weights3); + { + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 7) * wh) : (FLOAT4)0); + + DOT16X16(in0, weights0, out.s0); + DOT16X16(in1, weights1, out.s0); + DOT16X16(in0, weights2, out.s1); + DOT16X16(in1, weights3, out.s1); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 7) * wh) : (FLOAT4)0); + + DOT16X16(in0, weights0, out1.s0); + DOT16X16(in1, weights1, out1.s0); + DOT16X16(in0, weights2, out1.s1); + DOT16X16(in1, weights3, out1.s1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 7) * wh) : (FLOAT4)0); + + DOT16X16(in0, weights0, out2.s0); + DOT16X16(in1, weights1, out2.s0); + DOT16X16(in0, weights2, out2.s1); + DOT16X16(in1, weights3, out2.s1); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 7) * wh) : (FLOAT4)0); + + DOT16X16(in0, weights0, out3.s0); + DOT16X16(in1, weights1, out3.s0); + DOT16X16(in0, weights2, out3.s1); + DOT16X16(in1, weights3, out3.s1); + } + #endif } -#endif + #endif + #endif //USE_LOW_BIT_WEIGHT_INT4 } -#endif -#endif //USE_LOW_BIT_WEIGHT_INT4 - out = bias0 + mad(out, Scale, sum * Offset); #ifdef RELU out = fmax(out, (COMPUTE_FLOAT2)0); #endif @@ -1220,7 +1202,6 @@ __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 #ifdef BACTH_BLOCK4 if(isValidBatch1){ out_offset += dstChannelC4 * height * width * 4; - out1 = bias0 + mad(out1, Scale, sum1 * Offset); #ifdef RELU out1 = fmax(out1, (COMPUTE_FLOAT2)0); #endif @@ -1233,7 +1214,6 @@ __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 } if(isValidBatch2){ out_offset += dstChannelC4 * height * width * 4; - out2 = bias0 + mad(out2, Scale, sum2 * Offset); #ifdef RELU out2 = fmax(out2, (COMPUTE_FLOAT2)0); #endif @@ -1246,7 +1226,6 @@ __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 } if(isValidBatch3){ out_offset += dstChannelC4 * height * width * 4; - out3 = bias0 + mad(out3, Scale, sum3 * Offset); #ifdef RELU out3 = fmax(out3, (COMPUTE_FLOAT2)0); #endif @@ -1262,15 +1241,17 @@ __kernel void gemm_conv_c2_image(GLOBAL_SIZE_DIM2 __kernel void gemm_conv_c1_image(GLOBAL_SIZE_DIM2 __global const FLOAT* input, __read_only image2d_t weight, - __global const float *dequantScale, - __global const float *dequantOffset, + __global const float *dequantScaleOffset, __global const FLOAT *bias, __global FLOAT* output, __private const int dstChannelC4, __private const int srcChannelC4, + __private const int srcChannel, __private const int batch, __private const int height, - __private const int width) { + __private const int width, + __private const int blockNum, + __private const int blockDim) { const int out_c_w_idx = get_global_id(0); //c/4 w const int out_b_h_idx = get_global_id(1); //b h UNIFORM_BOUNDRY_CHECK(out_c_w_idx, out_b_h_idx); @@ -1285,17 +1266,13 @@ __kernel void gemm_conv_c1_image(GLOBAL_SIZE_DIM2 const int out_h_idx = out_b_h_idx % height; COMPUTE_FLOAT bias0 = bias[out_c_idx]; - COMPUTE_FLOAT out = 0; - COMPUTE_FLOAT sum = 0; + COMPUTE_FLOAT out = bias0; int input_offset = ((out_b_idx * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int out_offset = (((out_b_idx * dstChannelC4 + out_c_idx/4)* height + out_h_idx) * width + out_w_idx) * 4 + (out_c_idx%4); -#ifndef WIDTH_HEIGHT_1 int wh = width * height * 4; -#endif #ifdef BACTH_BLOCK4 - COMPUTE_FLOAT sum1 = 0, sum2 = 0, sum3 = 0; - COMPUTE_FLOAT out1 = 0, out2 = 0, out3 = 0; + COMPUTE_FLOAT out1 = bias0, out2 = bias0, out3 = bias0; int input_offset1 = (((out_b_idx + 1) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset2 = (((out_b_idx + 2) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; int input_offset3 = (((out_b_idx + 3) * srcChannelC4 * height + out_h_idx) * width + out_w_idx) * 4; @@ -1303,356 +1280,340 @@ __kernel void gemm_conv_c1_image(GLOBAL_SIZE_DIM2 bool isValidBatch2 = out_b_idx + 2 < batch; bool isValidBatch3 = out_b_idx + 3 < batch; #endif - const COMPUTE_FLOAT Scale = dequantScale[out_c_idx]; - const COMPUTE_FLOAT Offset = dequantOffset[out_c_idx]; - + #if (defined USE_LOW_BIT_WEIGHT_INT8) -#ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC16 = (srcChannelC4 + 3) >> 2; - for (int k = 0; k < srcChannelC16-1; k++) { -#else - for (int k = 0; k < srcChannelC4/4; k++) { -#endif -#ifndef WIDTH_HEIGHT_1 - int k4 = k * 4; -#endif - COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k)))); - { - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); -#endif - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); -#endif - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); -#endif - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; -#ifdef WIDTH_HEIGHT_1 - in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 16)); -#else - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); - in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); - in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); -#endif - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3); - } -#endif - } -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC16 - 1; - int k4 = k * 4; - COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k)))); - { - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); - sum += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); - sum1 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); - sum2 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out2); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in; - in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); - in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); - in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); - in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); - sum3 += in.s0 + in.s1 + in.s2 + in.s3 + in.s4 + in.s5 + in.s6 + in.s7 + in.s8 + in.s9 + in.sa + in.sb + in.sc + in.sd + in.se + in.sf; - DOT16X16(in, weights0, out3); - } -#endif - } -#endif + const int loop = (blockDim + 15) / 16; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + #else + const int loop_end = loop; + #endif #elif (defined USE_LOW_BIT_WEIGHT_INT4) -#ifdef INPUT_CHANNEL_LEAVE - const int srcChannelC32 = (srcChannelC4 + 7) >> 3; - for (int k = 0; k < srcChannelC32-1; k++) { -#else - for (int k = 0; k < srcChannelC4/8; k++) { + const int loop = (blockDim + 31) / 32; + #ifdef INPUT_CHANNEL_LEAVE + const int loop_end = max(loop - 1, 0); + #else + const int loop_end = loop; + #endif #endif -#ifndef WIDTH_HEIGHT_1 - int k8 = k * 8; -#endif - COMPUTE_FLOAT16 weights0, weights1; - { - uchar16 charWeightsInt4 = as_uchar16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k))); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); + + for (int i = 0; i < blockNum; ++i){ + int kindex = i * dstChannelC4 * 4 * 2; + COMPUTE_FLOAT2 ScaleOffset = CONVERT_COMPUTE_FLOAT2(vload2(out_c_idx, dequantScaleOffset + kindex)); + #if (defined USE_LOW_BIT_WEIGHT_INT8) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k4 = k << 2; + #endif + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + { + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out); + } + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out2); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + #ifdef WIDTH_HEIGHT_1 + in = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 16)); + #else + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 1) * wh)); + in.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 2) * wh)); + in.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k4 + 3) * wh)); + #endif + DOT16X16(in, weights0, out3); + } + #endif } + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 3) * wh)); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 7) * wh)); + int k = i * loop + loop_end; + int k4 = k << 2; + COMPUTE_FLOAT16 weights0 = CONVERT_COMPUTE_FLOAT16(as_char16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k)))) * ScaleOffset.s0 + ScaleOffset.s1; + { + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out); + } + PADZEROS(k, srcChannel, weights0); + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out2); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in; + in.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k4 * wh)); + in.s4567 = CONVERT_COMPUTE_FLOAT4(k4 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 1) * wh) : (FLOAT4)0); + in.s89ab = CONVERT_COMPUTE_FLOAT4(k4 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 2) * wh) : (FLOAT4)0); + in.scdef = CONVERT_COMPUTE_FLOAT4(k4 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k4 + 3) * wh) : (FLOAT4)0); + DOT16X16(in, weights0, out3); + } + #endif + } + #endif + #elif (defined USE_LOW_BIT_WEIGHT_INT4) + for (int j = 0; j < loop_end; j++) { + int k = i * loop + j; + #ifndef WIDTH_HEIGHT_1 + int k8 = k << 3; + #endif + COMPUTE_FLOAT16 weights0, weights1; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + { + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 3) * wh)); -#endif - sum += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out); - DOT16X16(in1, weights1, out); - } + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out); + DOT16X16(in1, weights1, out); + } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 3) * wh)); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 7) * wh)); -#endif - sum1 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum1 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out1); - DOT16X16(in1, weights1, out1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 3) * wh)); + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset1 + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 3) * wh)); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 7) * wh)); -#endif - sum2 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum2 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out2); - DOT16X16(in1, weights1, out2); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in0, in1; -#ifdef WIDTH_HEIGHT_1 - in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32)); - in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32 + 16)); -#else - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 1) * wh)); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 2) * wh)); - in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 3) * wh)); + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out1); + DOT16X16(in1, weights1, out1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset2 + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 3) * wh)); - in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 4) * wh)); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 5) * wh)); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 6) * wh)); - in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 7) * wh)); -#endif - sum3 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum3 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out3); - DOT16X16(in1, weights1, out3); - } -#endif - } + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out2); + DOT16X16(in1, weights1, out2); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in0, in1; + #ifdef WIDTH_HEIGHT_1 + in0 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32)); + in1 = CONVERT_COMPUTE_FLOAT16(vload16(0, input + input_offset3 + k * 32 + 16)); + #else + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 1) * wh)); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 2) * wh)); + in0.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 3) * wh)); -#ifdef INPUT_CHANNEL_LEAVE - { - int k = srcChannelC32 - 1; - int k8 = k * 8; - COMPUTE_FLOAT16 weights0, weights1; - { - uchar16 charWeightsInt4 = as_uchar16(read_imagef(weight, SAMPLER, (int2)(out_c_idx, k))); - char16 charWeights0 = 0; - char16 charWeights1 = 0; - UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); - weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0); - weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1); + in1.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 4) * wh)); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 5) * wh)); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 6) * wh)); + in1.scdef = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + (k8 + 7) * wh)); + #endif + DOT16X16(in0, weights0, out3); + DOT16X16(in1, weights1, out3); + } + #endif } + #ifdef INPUT_CHANNEL_LEAVE { - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 3) * wh) : (FLOAT4)0); + int k = i * loop + loop_end; + int k8 = k << 3; + COMPUTE_FLOAT16 weights0, weights1; + { + uchar16 charWeightsInt4 = as_uchar16(read_imagei(weight, SAMPLER, (int2)(out_c_idx, k))); + char16 charWeights0 = 0; + char16 charWeights1 = 0; + UCHAR16_TO_2CHAR16(charWeights0, charWeights1, charWeightsInt4); + weights0 = CONVERT_COMPUTE_FLOAT16(charWeights0) * ScaleOffset.s0 + ScaleOffset.s1; + weights1 = CONVERT_COMPUTE_FLOAT16(charWeights1) * ScaleOffset.s0 + ScaleOffset.s1; + } + PADZEROS(k, srcChannel, weights0); + PADZEROS(k + 15, srcChannel, weights1); + { + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 7) * wh) : (FLOAT4)0); + DOT16X16(in0, weights0, out); + DOT16X16(in1, weights1, out); + } - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset + (k8 + 7) * wh) : (FLOAT4)0); - sum += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in0, weights0, out); - DOT16X16(in1, weights1, out); - } -#ifdef BACTH_BLOCK4 - if(isValidBatch1){ - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < vload4(0, input + input_offset1 + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < vload4(0, input + input_offset1 + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < vload4(0, input + input_offset1 + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 7) * wh) : (FLOAT4)0); - sum1 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum1 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in2, weights0, out1); - DOT16X16(in3, weights1, out1); - } - if(isValidBatch2){ - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < vload4(0, input + input_offset2 + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < vload4(0, input + input_offset2 + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < vload4(0, input + input_offset2 + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 7) * wh) : (FLOAT4)0); - sum2 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum2 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in2, weights0, out2); - DOT16X16(in3, weights1, out2); - } - if(isValidBatch3){ - COMPUTE_FLOAT16 in0, in1; - in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k8 * wh)); - in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < vload4(0, input + input_offset3 + (k8 + 1) * wh) : (FLOAT4)0); - in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < vload4(0, input + input_offset3 + (k8 + 2) * wh) : (FLOAT4)0); - in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < vload4(0, input + input_offset3 + (k8 + 3) * wh) : (FLOAT4)0); - - in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 4) * wh) : (FLOAT4)0); - in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 5) * wh) : (FLOAT4)0); - in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 6) * wh) : (FLOAT4)0); - in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 7) * wh) : (FLOAT4)0); - sum3 += in0.s0 + in0.s1 + in0.s2 + in0.s3 + in0.s4 + in0.s5 + in0.s6 + in0.s7 + in0.s8 + in0.s9 + in0.sa + in0.sb + in0.sc + in0.sd + in0.se + in0.sf; - sum3 += in1.s0 + in1.s1 + in1.s2 + in1.s3 + in1.s4 + in1.s5 + in1.s6 + in1.s7 + in1.s8 + in1.s9 + in1.sa + in1.sb + in1.sc + in1.sd + in1.se + in1.sf; - DOT16X16(in2, weights0, out3); - DOT16X16(in3, weights1, out3); + #ifdef BACTH_BLOCK4 + if(isValidBatch1){ + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset1 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset1 + (k8 + 7) * wh) : (FLOAT4)0); + DOT16X16(in0, weights0, out1); + DOT16X16(in1, weights1, out1); + } + if(isValidBatch2){ + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset2 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset2 + (k8 + 7) * wh) : (FLOAT4)0); + DOT16X16(in0, weights0, out2); + DOT16X16(in1, weights1, out2); + } + if(isValidBatch3){ + COMPUTE_FLOAT16 in0, in1; + in0.s0123 = CONVERT_COMPUTE_FLOAT4(vload4(0, input + input_offset3 + k8 * wh)); + in0.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 1 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 1) * wh) : (FLOAT4)0); + in0.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 2 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 2) * wh) : (FLOAT4)0); + in0.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 3 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 3) * wh) : (FLOAT4)0); + + in1.s0123 = CONVERT_COMPUTE_FLOAT4(k8 + 4 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 4) * wh) : (FLOAT4)0); + in1.s4567 = CONVERT_COMPUTE_FLOAT4(k8 + 5 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 5) * wh) : (FLOAT4)0); + in1.s89ab = CONVERT_COMPUTE_FLOAT4(k8 + 6 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 6) * wh) : (FLOAT4)0); + in1.scdef = CONVERT_COMPUTE_FLOAT4(k8 + 7 < srcChannelC4 ? vload4(0, input + input_offset3 + (k8 + 7) * wh) : (FLOAT4)0); + DOT16X16(in0, weights0, out3); + DOT16X16(in1, weights1, out3); + } + #endif } -#endif + #endif + #endif //USE_LOW_BIT_WEIGHT_INT4 } -#endif -#endif //USE_LOW_BIT_WEIGHT_INT4 - out = bias0 + mad(out, Scale, sum * Offset); #ifdef RELU - out = fmax(out, 0); + out = fmax(out, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out = clamp(out, 0, 6); + out = clamp(out, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out; #ifdef BACTH_BLOCK4 if(isValidBatch1){ out_offset += dstChannelC4 * height * width * 4; - out1 = bias0 + mad(out1, Scale, sum1 * Offset); #ifdef RELU - out1 = fmax(out1, 0); + out1 = fmax(out1, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out1 = clamp(out1, 0, 6); + out1 = clamp(out1, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out1; } if(isValidBatch2){ out_offset += dstChannelC4 * height * width * 4; - out2 = bias0 + mad(out2, Scale, sum2 * Offset); #ifdef RELU - out2 = fmax(out2, 0); + out2 = fmax(out2, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out1 = clamp(out2, 0, 6); + out1 = clamp(out2, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out2; } if(isValidBatch3){ out_offset += dstChannelC4 * height * width * 4; - out3 = bias0 + mad(out3, Scale, sum3 * Offset); #ifdef RELU - out3 = fmax(out3, 0); + out3 = fmax(out3, (COMPUTE_FLOAT)0); #endif #ifdef RELU6 - out3 = clamp(out3, 0, 6); + out3 = clamp(out3, (COMPUTE_FLOAT)0, (COMPUTE_FLOAT)6); #endif output[out_offset] = out3; diff --git a/source/backend/opencl/execution/cl/groupnorm_buf.cl b/source/backend/opencl/execution/cl/groupnorm_buf.cl new file mode 100644 index 000000000..59e848dff --- /dev/null +++ b/source/backend/opencl/execution/cl/groupnorm_buf.cl @@ -0,0 +1,243 @@ +#ifdef MNN_SUPPORT_FP16 +#pragma OPENCL EXTENSION cl_khr_fp16 : enable +#endif + +__kernel void groupnorm_plain_buf(__private int global_dim0, __private int global_dim1, __private int global_dim2, +#ifdef DOUBLE_INPUTS + __global const FLOAT * input0, + __global const FLOAT * input1, +#else + __global const FLOAT * input, +#endif + __global FLOAT * output, + __private const int area, + __private const int group, + __private const int inside, + __private const int outside, +#ifdef GAMMA_BETA + __global const FLOAT *gamma, + __global const FLOAT *beta, +#endif + __private float epsilon){ + int3 pos = (int3)(get_global_id(0), get_global_id(1), get_global_id(2)); + float local sum[LOCAL_SIZE]; + if (pos.x < global_dim0 && pos.y < global_dim1 && pos.z < global_dim2) { + const int idx_out = pos.z; + const int lid = get_local_id(0); + const int offset = idx_out * inside; + const int inside_v4 = (inside + 3) >> 2; + +#ifdef DOUBLE_INPUTS + // The product of W and H is a multiple of 4 + #ifdef WH_4 + float4 in_sum = 0; + int index = lid; + for(; index < inside_v4; index+=LOCAL_SIZE){ + float4 in0 = convert_float4(vload4(index, input0 + offset)); + in_sum += in0; + float in1 = input1[idx_out * (inside/area) + index / (area/4)]; + in_sum += (float4)(in1, in1, in1, in1); + } + sum[lid] = in_sum.x + in_sum.y + in_sum.z+ in_sum.w; + + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = LOCAL_SIZE/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + + + float4 mean = sum[0] / (float4)inside; + + in_sum = 0; + index = lid; + for(; index < inside_v4; index+=LOCAL_SIZE){ + float4 in0 = convert_float4(vload4(index, input0 + offset)); + float in1 = input1[idx_out * (inside/area) + index / (area/4)]; + in_sum += (in0 + (float4)(in1, in1, in1, in1) - mean) * (in0 + (float4)in1 - mean); + } + sum[lid] = in_sum.x + in_sum.y + in_sum.z + in_sum.w; + + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = LOCAL_SIZE/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + float4 square_sum = sum[0] / (float4)inside; + float4 value = (float4)1.0f / (float4)sqrt(square_sum + (float4)epsilon); + + for(int i = lid; i < inside_v4; i+=LOCAL_SIZE){ + float4 in0 = convert_float4(vload4(i, input0 + offset)); + float in1 = input1[idx_out * (inside/area) + i / (area/4)]; + float4 out = (in0 + (float4)(in1, in1, in1, in1) - mean) * value; + + #ifdef GAMMA_BETA + int offset_gamma_beta = (idx_out % group) * inside/area + i / (area/4); + out = out * (float4)((float)gamma[offset_gamma_beta]) + (float4)((float)beta[offset_gamma_beta]); + #endif + + #ifdef SWISH + out = out * native_recip((float4)1+native_exp(convert_float4(-out))); + #endif + vstore4(CONVERT_FLOAT4(out), i, output + offset); + } + #else + + float in_sum = 0; + int index = lid; + for(; index < inside; index+=LOCAL_SIZE){ + float in0 = input0[offset + index]; + in_sum += in0; + float in1 = input1[idx_out * (inside/area) + index / area]; + in_sum += in1; + } + sum[lid] = in_sum; + + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = LOCAL_SIZE/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + + + float mean = sum[0] / inside; + + in_sum = 0; + index = lid; + for(; index < inside; index+=LOCAL_SIZE){ + float in0 = input0[offset + index]; + float in1 = input1[idx_out * (inside/area) + index / area]; + in_sum += (in0 + in1 - mean) * (in0 + in1 - mean); + } + sum[lid] = in_sum; + + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = LOCAL_SIZE/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + float square_sum = sum[0] / inside; + float value = 1.0f / sqrt(square_sum + epsilon); + + for(int i = lid; i < inside; i+=LOCAL_SIZE){ + float in0 = input0[offset + i]; + float in1 = input1[idx_out * (inside/area) + i / area]; + float out = (in0 + in1 - mean) * value; + + #ifdef GAMMA_BETA + int offset_gamma_beta = (idx_out % group) * inside/area + i / area; + out = out * (float)gamma[offset_gamma_beta] + (float)beta[offset_gamma_beta]; + #endif + + #ifdef SWISH + out = out * native_recip(1.0+native_exp(-out)); + #endif + output[offset+i] = (FLOAT)out; + } + + #endif +#else + const int inside_remain = inside - ((inside_v4-1) << 2); + + float4 in_sum = 0; + int index = lid; + for(; index < inside_v4 - 1; index+=LOCAL_SIZE){ + float4 in = convert_float4(vload4(index, input + offset)); + in_sum += in; + } + sum[lid] = in_sum.x + in_sum.y + in_sum.z+ in_sum.w; + + float4 in_left = 0; + if(index == inside_v4 - 1) { + in_left = convert_float4(vload4(inside_v4 - 1, input + offset)); + sum[lid] = sum[lid] + in_left.x; + if(inside_remain > 1) { + sum[lid] = sum[lid] + in_left.y; + } + if(inside_remain > 2) { + sum[lid] = sum[lid] + in_left.z; + } + if(inside_remain > 3) { + sum[lid] = sum[lid] + in_left.w; + } + } + + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = LOCAL_SIZE/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + + float4 mean = sum[0] / (float4)inside; + + in_sum = 0; + index = lid; + for(; index < inside_v4 - 1; index+=LOCAL_SIZE){ + float4 in = convert_float4(vload4(index, input + offset)); + in_sum += (in - mean) * (in - mean); + } + sum[lid] = in_sum.x + in_sum.y + in_sum.z + in_sum.w; + + if(index == inside_v4 - 1) { + float4 in_left = convert_float4(vload4(inside_v4 - 1, input + offset)); + in_sum = (in_left - mean) * (in_left - mean); + sum[lid] = sum[lid] + in_sum.x; + if(inside_remain > 1) { + sum[lid] = sum[lid] + in_sum.y; + } + if(inside_remain > 2) { + sum[lid] = sum[lid] + in_sum.z; + } + if(inside_remain > 3) { + sum[lid] = sum[lid] + in_sum.w; + } + } + barrier(CLK_LOCAL_MEM_FENCE); + for(int i = LOCAL_SIZE/2; i > 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + float4 square_sum = sum[0] / (float4)inside; + float4 value = (float4)1.0f / (float4)sqrt(square_sum + (float4)epsilon); + + // The product of W and H is a multiple of 4 + #ifdef WH_4 + for(int i = lid; i < inside_v4; i+=LOCAL_SIZE){ + float4 in = convert_float4(vload4(i, input + offset)); + float4 out = (in - mean) * value; + + #ifdef GAMMA_BETA + int offset_gamma_beta = (idx_out % group) * inside/area + i / (area/4); + out = out * (float4)((float)gamma[offset_gamma_beta]) + (float4)((float)beta[offset_gamma_beta]); + #endif + + #ifdef SWISH + out = out * native_recip((float4)1+native_exp(convert_float4(-out))); + #endif + vstore4(CONVERT_FLOAT4(out), i, output + offset); + } + #else + for(int i = lid; i < inside; i+=LOCAL_SIZE){ + float in = input[offset+i]; + float out = (in - mean.x) * value.x; + + #ifdef GAMMA_BETA + int offset_gamma_beta = (idx_out % group) * inside/area + i / area; + out = out * (float)gamma[offset_gamma_beta] + (float)beta[offset_gamma_beta]; + #endif + + #ifdef SWISH + out = out * native_recip(1.0+native_exp(-out)); + #endif + output[offset+i] = (FLOAT)out; + } + #endif +#endif + } +} diff --git a/source/backend/opencl/execution/cl/layernorm_buf.cl b/source/backend/opencl/execution/cl/layernorm_buf.cl index 3608a7af5..3ee18e085 100644 --- a/source/backend/opencl/execution/cl/layernorm_buf.cl +++ b/source/backend/opencl/execution/cl/layernorm_buf.cl @@ -249,14 +249,15 @@ __kernel void layernorm_plain_buf(__private int global_dim0, __private int globa const int inside_remain = inside - ((inside_v4-1) << 2); COMPUTE_FLOAT4 in_sum = 0; - for(int i = lid; i < inside_v4 - 1; i+=LOCAL_SIZE){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(i, input + offset)); + int index = lid; + for(; index < inside_v4 - 1; index+=LOCAL_SIZE){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(index, input + offset)); in_sum += in; } sum[lid] = in_sum.x + in_sum.y + in_sum.z+ in_sum.w; COMPUTE_FLOAT4 in_left = 0; - if(lid == inside_v4 - 1) { + if(index == inside_v4 - 1) { in_left = CONVERT_COMPUTE_FLOAT4(vload4(inside_v4 - 1, input + offset)); sum[lid] = sum[lid] + in_left.x; if(inside_remain > 1) { @@ -280,13 +281,14 @@ __kernel void layernorm_plain_buf(__private int global_dim0, __private int globa COMPUTE_FLOAT4 mean = sum[0] / (COMPUTE_FLOAT4)inside; in_sum = 0; - for(int i = lid; i < inside_v4 - 1; i+=LOCAL_SIZE){ - COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(i, input + offset)); + index = lid; + for(; index < inside_v4 - 1; index+=LOCAL_SIZE){ + COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(index, input + offset)); in_sum += (in - mean) * (in - mean); } sum[lid] = in_sum.x + in_sum.y + in_sum.z + in_sum.w; - if(lid == inside_v4 - 1) { + if(index == inside_v4 - 1) { COMPUTE_FLOAT4 in_left = CONVERT_COMPUTE_FLOAT4(vload4(inside_v4 - 1, input + offset)); in_sum = (in_left - mean) * (in_left - mean); sum[lid] = sum[lid] + in_sum.x; @@ -308,11 +310,7 @@ __kernel void layernorm_plain_buf(__private int global_dim0, __private int globa } COMPUTE_FLOAT4 square_sum = sum[0] / (COMPUTE_FLOAT4)inside; COMPUTE_FLOAT4 value = (COMPUTE_FLOAT4)1.0f / (COMPUTE_FLOAT4)sqrt(square_sum + (COMPUTE_FLOAT4)epsilon); - /* - if(pos.x == 0) { - printf("ln: %d, mean:%f square:%f, value:%f\n", pos.z, (float)mean.x, (float)sum[0], (float)value.x); - } - */ + for(int i = lid; i < inside_v4; i+=LOCAL_SIZE){ COMPUTE_FLOAT4 in = CONVERT_COMPUTE_FLOAT4(vload4(i, input + offset)); #ifdef GAMMA_BETA diff --git a/source/backend/opencl/execution/cl/loop_buf.cl b/source/backend/opencl/execution/cl/loop_buf.cl index c73eaa11a..de7cb5725 100644 --- a/source/backend/opencl/execution/cl/loop_buf.cl +++ b/source/backend/opencl/execution/cl/loop_buf.cl @@ -3,13 +3,13 @@ #endif #define PI 3.141592653589f #ifndef WGSW - #define WGSW 64 // work-group handle size W dimension + #define WGSW 32 // work-group handle size W dimension #endif #ifndef WGSC - #define WGSC 64 // work-group handle size C dimension + #define WGSC 32 // work-group handle size C dimension #endif #ifndef WGSH - #define WGSH 64 // work-group handle size H dimension + #define WGSH 32 // work-group handle size H dimension #endif #ifndef TSW #define TSW 8 // thread handle size W dimension @@ -409,6 +409,7 @@ __kernel void broadcast_binary_buf(__private int global_dim0, __private int glob const int ho = pos.y; const int co = pos.z % channel_block; const int no = pos.z / channel_block; + const int output_offset = ((((no * channel_block) + co) * dst_height + ho) * dst_width + wo) * 4; int co4 = co << 2; int4 covec = (int4)(co4 % dst_channel, (co4 + 1) % dst_channel, (co4 + 2) % dst_channel, (co4 + 3) % dst_channel); int4 out_offset = ((no * dst_channel + covec) * dst_height + ho) * dst_width + wo; @@ -416,56 +417,129 @@ __kernel void broadcast_binary_buf(__private int global_dim0, __private int glob int4 h = out_offset % dst_size.s2; out_offset /= dst_size.s2; int4 c = out_offset % dst_size.s1; out_offset /= dst_size.s1; int4 n = out_offset % dst_size.s0; - const int src0_channel_block = (src0C4_size.z + 3) / 4; - const int src1_channel_block = (src1C4_size.z + 3) / 4; float4 in0, in1; - float* in0_ptr = (float*)&in0; + +#ifdef BROADCAST_INPUT1 + in0 = convert_float4(vload4(0, input0 + output_offset)); + const int src1_channel_block = (src1C4_size.y + 3) / 4; float* in1_ptr = (float*)&in1; - { - int4 w0 = w % (src0_size.s3 * src0_size.s4); - int4 h0 = h % src0_size.s2; - int4 c0 = c % src0_size.s1; - int4 n0 = n % src0_size.s0; + int4 w0 = w % (src1_size.s3 * src1_size.s4); + int4 h0 = h % src1_size.s2; + int4 c0 = c % src1_size.s1; + int4 n0 = n % src1_size.s0; int* w0_ptr = (int*)&w0; int* h0_ptr = (int*)&h0; int* c0_ptr = (int*)&c0; int* n0_ptr = (int*)&n0; for(int i = 0; i < 4; ++i){ - int c4offset = ((n0_ptr[i] * src0_size.s1 + c0_ptr[i]) * src0_size.s2 + h0_ptr[i]) * src0_size.s3 * src0_size.s4 + w0_ptr[i]; - int wc4 = c4offset % src0C4_size.x; c4offset /= src0C4_size.x; - int hc4 = c4offset % src0C4_size.y; c4offset /= src0C4_size.y; - int cc4 = c4offset % src0C4_size.z; c4offset /= src0C4_size.z; - int nc4 = c4offset % src0C4_size.w; + int c4offset = ((n0_ptr[i] * src1_size.s1 + c0_ptr[i]) * src1_size.s2 + h0_ptr[i]) * src1_size.s3 * src1_size.s4 + w0_ptr[i]; + int wc4 = c4offset % src1C4_size.w; c4offset /= src1C4_size.w; + int hc4 = c4offset % src1C4_size.z; c4offset /= src1C4_size.z; + int cc4 = c4offset % src1C4_size.y; c4offset /= src1C4_size.y; + int nc4 = c4offset % src1C4_size.x; int cc4_offset = cc4 / 4; int cc4_remain = cc4 % 4; - in0_ptr[i] = (float)input0[((((nc4 * src0_channel_block) + cc4_offset) * src0C4_size.y + hc4) * src0C4_size.x + wc4) * 4 + cc4_remain]; + in1_ptr[i] = (float)input1[((((nc4 * src1_channel_block) + cc4_offset) * src1C4_size.z + hc4) * src1C4_size.w + wc4) * 4 + cc4_remain]; } } - +#else + const int src0_channel_block = (src0C4_size.y + 3) / 4; + float* in0_ptr = (float*)&in0; { - int4 w0 = w % (src1_size.s3 * src1_size.s4); - int4 h0 = h % src1_size.s2; - int4 c0 = c % src1_size.s1; - int4 n0 = n % src1_size.s0; + int4 w0 = w % (src0_size.s3 * src0_size.s4); + int4 h0 = h % src0_size.s2; + int4 c0 = c % src0_size.s1; + int4 n0 = n % src0_size.s0; int* w0_ptr = (int*)&w0; int* h0_ptr = (int*)&h0; int* c0_ptr = (int*)&c0; int* n0_ptr = (int*)&n0; for(int i = 0; i < 4; ++i){ - int c4offset = ((n0_ptr[i] * src1_size.s1 + c0_ptr[i]) * src1_size.s2 + h0_ptr[i]) * src1_size.s3 * src1_size.s4 + w0_ptr[i]; - int wc4 = c4offset % src1C4_size.x; c4offset /= src1C4_size.x; - int hc4 = c4offset % src1C4_size.y; c4offset /= src1C4_size.y; - int cc4 = c4offset % src1C4_size.z; c4offset /= src1C4_size.z; - int nc4 = c4offset % src1C4_size.w; + int c4offset = ((n0_ptr[i] * src0_size.s1 + c0_ptr[i]) * src0_size.s2 + h0_ptr[i]) * src0_size.s3 * src0_size.s4 + w0_ptr[i]; + int wc4 = c4offset % src0C4_size.w; c4offset /= src0C4_size.w; + int hc4 = c4offset % src0C4_size.z; c4offset /= src0C4_size.z; + int cc4 = c4offset % src0C4_size.y; c4offset /= src0C4_size.y; + int nc4 = c4offset % src0C4_size.x; int cc4_offset = cc4 / 4; int cc4_remain = cc4 % 4; - in1_ptr[i] = (float)input1[((((nc4 * src1_channel_block) + cc4_offset) * src1C4_size.y + hc4) * src1C4_size.x + wc4) * 4 + cc4_remain]; + in0_ptr[i] = (float)input0[((((nc4 * src0_channel_block) + cc4_offset) * src0C4_size.z + hc4) * src0C4_size.w + wc4) * 4 + cc4_remain]; } } + in1 = convert_float4(vload4(0, input1 + output_offset)); +#endif + float4 out = LOOP_BINARY_OPERATOR; + vstore4(CONVERT_OUTPUT4(out), 0, output + output_offset); + } +} + +__kernel void broadcast_binary_channel_equall_buf(__private int global_dim0, __private int global_dim1, __private int global_dim2, + __global OUTPUT_TYPE* output, __global INPUT_TYPE* input0, __global INPUT_TYPE* input1, + __private const int8 src0_size, //(batch, channel, height, width) + __private const int4 src0C4_size, // nc4hw4 + __private const int8 src1_size, + __private const int4 src1C4_size, + __private const int8 dst_size, + __private const int dst_width, + __private const int dst_height, + __private const int dst_channel, + __private const int channel_block) { + int3 pos = (int3)(get_global_id(0), get_global_id(1), get_global_id(2)); + + if (pos.x < global_dim0 && pos.y < global_dim1 && pos.z < global_dim2) { + const int wo = pos.x; + const int ho = pos.y; + const int co = pos.z % channel_block; + const int no = pos.z / channel_block; + const int output_offset = ((((no * channel_block) + co) * dst_height + ho) * dst_width + wo) * 4; +#ifdef BROADCAST_INPUT1 + const int src1_channel_block = (src1C4_size.y + 3) / 4; + const int input_offset = (((((no % src1_size.s0) * src1_channel_block) + co) * src1C4_size.z + (ho % src1_size.s2)) * src1C4_size.w + (wo % (src1_size.s3 * src1_size.s4))) * 4; + float4 in0 = convert_float4(vload4(0, input0 + output_offset)); + float4 in1 = convert_float4(vload4(0, input1 + input_offset)); +#else + const int src0_channel_block = (src0C4_size.y + 3) / 4; + const int input_offset = (((((no % src0_size.s0) * src0_channel_block) + co) * src0C4_size.z + (ho % src0_size.s2)) * src0C4_size.w + (wo % (src0_size.s3 * src0_size.s4))) * 4; + float4 in0 = convert_float4(vload4(0, input0 + input_offset)); + float4 in1 = convert_float4(vload4(0, input1 + output_offset)); +#endif + float4 out = LOOP_BINARY_OPERATOR; + vstore4(CONVERT_OUTPUT4(out), 0, output + output_offset); + } +} + +//channel = 1 and dimmision = 1 +__kernel void broadcast_binary_dimmision1_channel1_buf(__private int global_dim0, __private int global_dim1, __private int global_dim2, + __global OUTPUT_TYPE* output, __global INPUT_TYPE* input0, __global INPUT_TYPE* input1, + __private const int8 src0_size, //(batch, channel, height, width) + __private const int4 src0C4_size, // nc4hw4 + __private const int8 src1_size, + __private const int4 src1C4_size, + __private const int8 dst_size, + __private const int dst_width, + __private const int dst_height, + __private const int dst_channel, + __private const int channel_block) { + int3 pos = (int3)(get_global_id(0), get_global_id(1), get_global_id(2)); + + if (pos.x < global_dim0 && pos.y < global_dim1 && pos.z < global_dim2) { + const int wo = pos.x; + const int ho = pos.y; + const int co = pos.z % channel_block; + const int no = pos.z / channel_block; + const int output_offset = ((((no * channel_block) + co) * dst_height + ho) * dst_width + wo) * 4; +#ifdef BROADCAST_INPUT1 + const int input_offset = ((no % src1_size.s0) * src1_size.s2 + (ho % src1_size.s2)) * src1_size.s3 * src1_size.s4 + (wo % (src1_size.s3 * src1_size.s4)); + float4 in0 = convert_float4(vload4(0, input0 + output_offset)); + float4 in1 = (float4)(input1[input_offset]); +#else + const int input_offset = ((no % src0_size.s0) * src0_size.s2 + (ho % src0_size.s2)) * src0_size.s3 * src0_size.s4 + (wo % (src0_size.s3 * src0_size.s4)); + float4 in0 = (float4)(input0[input_offset]); + float4 in1 = convert_float4(vload4(0, input1 + output_offset)); +#endif float4 out = LOOP_BINARY_OPERATOR; - vstore4(CONVERT_OUTPUT4(out), 0, output + ((((no * channel_block) + co) * dst_height + ho) * dst_width + wo) * 4); + vstore4(CONVERT_OUTPUT4(out), 0, output + output_offset); } } #endif diff --git a/source/backend/opencl/execution/cl/matmul_params_buf.cl b/source/backend/opencl/execution/cl/matmul_params_buf.cl index 90f91c474..601dc50e6 100644 --- a/source/backend/opencl/execution/cl/matmul_params_buf.cl +++ b/source/backend/opencl/execution/cl/matmul_params_buf.cl @@ -74,37 +74,6 @@ #define GLOBAL_MEM_FENCE 0 // Global synchronisation barrier for potential better performance #endif -#ifndef SUBGROUP_SHUFFLING_NVIDIA_PRE_VOLTA - #define SUBGROUP_SHUFFLING_NVIDIA_PRE_VOLTA 0 -#endif -#ifndef SUBGROUP_SHUFFLING_NVIDIA_POST_VOLTA - #define SUBGROUP_SHUFFLING_NVIDIA_POST_VOLTA 0 -#endif -#ifndef SUBGROUP_SHUFFLING_INTEL - #define SUBGROUP_SHUFFLING_INTEL 0 -#endif -#ifndef USE_SUBGROUP_SHUFFLING - #define USE_SUBGROUP_SHUFFLING 0 // Optionally enables subgroup shuffling for Intel GPUs -#endif - -// Intel subgroups (https://www.khronos.org/registry/OpenCL/extensions/intel/cl_intel_subgroups.html) -#if USE_SUBGROUP_SHUFFLING == 1 && SUBGROUP_SHUFFLING_INTEL == 1 - #pragma OPENCL EXTENSION cl_intel_subgroups: enable - #define SUBGROUP_SIZE 8 // Assumes subgroup size is always 8 on Intel GPUs -#endif - -// NVIDIA warps as subgroups using inline PTX (https://docs.nvidia.com/cuda/inline-ptx-assembly/index.html) -#if USE_SUBGROUP_SHUFFLING == 1 - #if SUBGROUP_SHUFFLING_NVIDIA_PRE_VOLTA == 1 || SUBGROUP_SHUFFLING_NVIDIA_POST_VOLTA == 1 - #define SUBGROUP_SIZE 32 // Assumes subgroup size is always 32 on NVIDIA GPUs - #endif -#endif - -#if NWI != SUBGROUP_SIZE || MDIMC < SUBGROUP_SIZE - #undef USE_SUBGROUP_SHUFFLING - #define USE_SUBGROUP_SHUFFLING 0 // Disables subgroups in case the assumptions don't hold -#endif - // Half-precision #if PRECISION == 16 typedef half real; @@ -274,29 +243,8 @@ // ================================================================================================= -// Shuffled workgroup indices to avoid partition camping, see below. For specific devices, this is -// enabled (see src/routine.cc). -#ifndef USE_STAGGERED_INDICES - #define USE_STAGGERED_INDICES 0 -#endif - -// Staggered/shuffled group indices to avoid partition camping (AMD GPUs). Formula's are taken from: -// http://docs.nvidia.com/cuda/samples/6_Advanced/transpose/doc/MatrixTranspose.pdf -// More details: https://github.com/CNugteren/CLBlast/issues/53 -#if USE_STAGGERED_INDICES == 1 && GEMMK == 0 - INLINE_FUNC int GetGroupIDFlat() { - return get_group_id(0) + get_num_groups(0) * get_group_id(1); - } - INLINE_FUNC int GetGroupID1() { - return (GetGroupIDFlat()) % get_num_groups(1); - } - INLINE_FUNC int GetGroupID0() { - return ((GetGroupIDFlat() / get_num_groups(1)) + GetGroupID1()) % get_num_groups(0); - } -#else INLINE_FUNC int GetGroupID1() { return get_group_id(1); } INLINE_FUNC int GetGroupID0() { return get_group_id(0); } -#endif // ================================================================================================= @@ -373,6 +321,48 @@ INLINE_FUNC realM InitAccRegisters() { return result; } +INLINE_FUNC realN InitAccRegistersN() { + realN result; + #if VWN == 1 + SetToZero(result); + #elif VWN == 2 + SetToZero(result.x); + SetToZero(result.y); + #elif VWN == 4 + SetToZero(result.x); + SetToZero(result.y); + SetToZero(result.z); + SetToZero(result.w); + #elif VWN == 8 + SetToZero(result.s0); + SetToZero(result.s1); + SetToZero(result.s2); + SetToZero(result.s3); + SetToZero(result.s4); + SetToZero(result.s5); + SetToZero(result.s6); + SetToZero(result.s7); + #elif VWN == 16 + SetToZero(result.s0); + SetToZero(result.s1); + SetToZero(result.s2); + SetToZero(result.s3); + SetToZero(result.s4); + SetToZero(result.s5); + SetToZero(result.s6); + SetToZero(result.s7); + SetToZero(result.s8); + SetToZero(result.s9); + SetToZero(result.sA); + SetToZero(result.sB); + SetToZero(result.sC); + SetToZero(result.sD); + SetToZero(result.sE); + SetToZero(result.sF); + #endif + return result; +} + // ================================================================================================= // Caches global off-chip memory into local (shared) memory on-chip. This function is specific for @@ -477,57 +467,6 @@ INLINE_FUNC realN GlobalToPrivateB(const __global realN* restrict bgm, const int } #endif -// ================================================================================================= -#if GEMMK == 1 - -// Caches global off-chip memory directly into per-thread private memory (registers). This function -// is specific for caching the A input matrix for kernel 1. -INLINE_FUNC realN GlobalToPrivateA2D(const __global real* restrict a_ptr, const int tid_y, const int _ni, - const int kSizeK, const int idk, const int _ki) { - #if PRECISION == 3232 || PRECISION == 6464 - const int a_index = (tid_y * NWI + _ni) * (kSizeK / VWN) + idk / VWN + _ki; - const __global realN* restrict agm = (const __global realN* restrict) a_ptr; - return agm[a_index]; - #else - const int a_index = (tid_y * NWI + _ni) * kSizeK + idk + _ki * VWN; - #if VWN == 1 - return a_ptr[a_index]; - #elif VWN == 2 - return vload2(0, a_ptr + a_index); - #elif VWN == 4 - return vload4(0, a_ptr + a_index); - #elif VWN == 8 - return vload8(0, a_ptr + a_index); - #elif VWN == 16 - return vload16(0, a_ptr + a_index); - #endif - #endif -} - -// Same as above, but now for the B input matrix -INLINE_FUNC realM GlobalToPrivateB2D(const __global real* restrict b_ptr, const int tid_x, const int _mi, - const int kSizeN, const int idk, const int _ki) { - #if PRECISION == 3232 || PRECISION == 6464 - const int b_index = (idk + _ki) * (kSizeN / VWM) + tid_x * (MWI / VWM) + _mi; - const __global realM* restrict bgm = (const __global realM* restrict) b_ptr; - return bgm[b_index]; - #else - const int b_index = (idk + _ki) * kSizeN + tid_x * MWI + _mi * VWM; - #if VWM == 1 - return b_ptr[b_index]; - #elif VWM == 2 - return vload2(0, b_ptr + b_index); - #elif VWM == 4 - return vload4(0, b_ptr + b_index); - #elif VWM == 8 - return vload8(0, b_ptr + b_index); - #elif VWM == 16 - return vload16(0, b_ptr + b_index); - #endif - #endif -} - -#endif // ================================================================================================= // Caches on-chip local memory into per-thread private memory (registers). This function is specific @@ -603,6 +542,52 @@ INLINE_FUNC realM MultiplyAddVector(realM cvec, const realM avec, const real bva return cvec; } +// The vectorised multiply-add function +INLINE_FUNC realN MultiplyAddVectorN(realN cvec, const real avec, const realN bval) { + #if USE_VECTOR_MAD == 1 + cvec += avec * bval; + #else + #if VWN == 1 + MultiplyAdd(cvec, avec, bval); + #elif VWN == 2 + MultiplyAdd(cvec.x , avec, bval.x); + MultiplyAdd(cvec.y , avec, bval.y); + #elif VWN == 4 + MultiplyAdd(cvec.x , avec, bval.x); + MultiplyAdd(cvec.y , avec, bval.y); + MultiplyAdd(cvec.z , avec, bval.z); + MultiplyAdd(cvec.w , avec, bval.w); + #elif VWN == 8 + MultiplyAdd(cvec.s0, avec, bval.s0); + MultiplyAdd(cvec.s1, avec, bval.s1); + MultiplyAdd(cvec.s2, avec, bval.s2); + MultiplyAdd(cvec.s3, avec, bval.s3); + MultiplyAdd(cvec.s4, avec, bval.s4); + MultiplyAdd(cvec.s5, avec, bval.s5); + MultiplyAdd(cvec.s6, avec, bval.s6); + MultiplyAdd(cvec.s7, avec, bval.s7); + #elif VWN == 16 + MultiplyAdd(cvec.s0, avec, bval.s0); + MultiplyAdd(cvec.s1, avec, bval.s1); + MultiplyAdd(cvec.s2, avec, bval.s2); + MultiplyAdd(cvec.s3, avec, bval.s3); + MultiplyAdd(cvec.s4, avec, bval.s4); + MultiplyAdd(cvec.s5, avec, bval.s5); + MultiplyAdd(cvec.s6, avec, bval.s6); + MultiplyAdd(cvec.s7, avec, bval.s7); + MultiplyAdd(cvec.s8, avec, bval.s8); + MultiplyAdd(cvec.s9, avec, bval.s9); + MultiplyAdd(cvec.sA, avec, bval.sA); + MultiplyAdd(cvec.sB, avec, bval.sB); + MultiplyAdd(cvec.sC, avec, bval.sC); + MultiplyAdd(cvec.sD, avec, bval.sD); + MultiplyAdd(cvec.sE, avec, bval.sE); + MultiplyAdd(cvec.sF, avec, bval.sF); + #endif + #endif + return cvec; +} + // ================================================================================================= // Merges the results in Cpm with the global array in Cgm. This also performs the multiplication @@ -737,7 +722,91 @@ INLINE_FUNC void StoreResultsN(__global realN* cgn, realN c_value, int index = idm * (kSizeN/VWN) + idn; realN result = 0; - result = c_value; + realN xval = c_value; + + // The final multiplication with alpha (in case beta == 0) + if (IsZero(beta)) { + #if VWN == 1 + Multiply(result, alpha, xval); + #elif VWN == 2 + Multiply(result.x, alpha, xval.x); + Multiply(result.y, alpha, xval.y); + #elif VWN == 4 + Multiply(result.x, alpha, xval.x); + Multiply(result.y, alpha, xval.y); + Multiply(result.z, alpha, xval.z); + Multiply(result.w, alpha, xval.w); + #elif VWN == 8 + Multiply(result.s0, alpha, xval.s0); + Multiply(result.s1, alpha, xval.s1); + Multiply(result.s2, alpha, xval.s2); + Multiply(result.s3, alpha, xval.s3); + Multiply(result.s4, alpha, xval.s4); + Multiply(result.s5, alpha, xval.s5); + Multiply(result.s6, alpha, xval.s6); + Multiply(result.s7, alpha, xval.s7); + #elif VWN == 16 + Multiply(result.s0, alpha, xval.s0); + Multiply(result.s1, alpha, xval.s1); + Multiply(result.s2, alpha, xval.s2); + Multiply(result.s3, alpha, xval.s3); + Multiply(result.s4, alpha, xval.s4); + Multiply(result.s5, alpha, xval.s5); + Multiply(result.s6, alpha, xval.s6); + Multiply(result.s7, alpha, xval.s7); + Multiply(result.s8, alpha, xval.s8); + Multiply(result.s9, alpha, xval.s9); + Multiply(result.sA, alpha, xval.sA); + Multiply(result.sB, alpha, xval.sB); + Multiply(result.sC, alpha, xval.sC); + Multiply(result.sD, alpha, xval.sD); + Multiply(result.sE, alpha, xval.sE); + Multiply(result.sF, alpha, xval.sF); + #endif + } + + // The final multiplication with alpha and the addition with beta*C + else { + realN yval = cgn[index]; + #if VWN == 1 + AXPBY(result, alpha, xval, beta, yval); + #elif VWN == 2 + AXPBY(result.x, alpha, xval.x, beta, yval.x); + AXPBY(result.y, alpha, xval.y, beta, yval.y); + #elif VWN == 4 + AXPBY(result.x, alpha, xval.x, beta, yval.x); + AXPBY(result.y, alpha, xval.y, beta, yval.y); + AXPBY(result.z, alpha, xval.z, beta, yval.z); + AXPBY(result.w, alpha, xval.w, beta, yval.w); + #elif VWN == 8 + AXPBY(result.s0, alpha, xval.s0, beta, yval.s0); + AXPBY(result.s1, alpha, xval.s1, beta, yval.s1); + AXPBY(result.s2, alpha, xval.s2, beta, yval.s2); + AXPBY(result.s3, alpha, xval.s3, beta, yval.s3); + AXPBY(result.s4, alpha, xval.s4, beta, yval.s4); + AXPBY(result.s5, alpha, xval.s5, beta, yval.s5); + AXPBY(result.s6, alpha, xval.s6, beta, yval.s6); + AXPBY(result.s7, alpha, xval.s7, beta, yval.s7); + #elif VWN == 16 + AXPBY(result.s0, alpha, xval.s0, beta, yval.s0); + AXPBY(result.s1, alpha, xval.s1, beta, yval.s1); + AXPBY(result.s2, alpha, xval.s2, beta, yval.s2); + AXPBY(result.s3, alpha, xval.s3, beta, yval.s3); + AXPBY(result.s4, alpha, xval.s4, beta, yval.s4); + AXPBY(result.s5, alpha, xval.s5, beta, yval.s5); + AXPBY(result.s6, alpha, xval.s6, beta, yval.s6); + AXPBY(result.s7, alpha, xval.s7, beta, yval.s7); + AXPBY(result.s8, alpha, xval.s8, beta, yval.s8); + AXPBY(result.s9, alpha, xval.s9, beta, yval.s9); + AXPBY(result.sA, alpha, xval.sA, beta, yval.sA); + AXPBY(result.sB, alpha, xval.sB, beta, yval.sB); + AXPBY(result.sC, alpha, xval.sC, beta, yval.sC); + AXPBY(result.sD, alpha, xval.sD, beta, yval.sD); + AXPBY(result.sE, alpha, xval.sE, beta, yval.sE); + AXPBY(result.sF, alpha, xval.sF, beta, yval.sF); + #endif + } + #ifdef BIAS realN xval = egn[idn]; @@ -783,43 +852,7 @@ INLINE_FUNC void StoreResultsN(__global realN* cgn, realN c_value, cgn[index] = result; } -// A common interface for subgroup functions - -#if USE_SUBGROUP_SHUFFLING == 1 -INLINE_FUNC int clblast_get_sub_group_local_id() { - - // Intel extension - #if SUBGROUP_SHUFFLING_INTEL == 1 - return get_sub_group_local_id(); - - // Nvidia inline PTX - #elif SUBGROUP_SHUFFLING_NVIDIA_PRE_VOLTA == 1 || SUBGROUP_SHUFFLING_NVIDIA_POST_VOLTA == 1 - int ret; - asm volatile("mov.u32 %0, %%laneid;" : "=r"(ret) ); - return ret; - #endif -} - -INLINE_FUNC realN clblast_sub_group_shuffle(realN reg, int src) { - - // Intel extension - #if SUBGROUP_SHUFFLING_INTEL == 1 - return intel_sub_group_shuffle(reg, src); - - // Nvidia inline PTX - // Volta and later requires .sync shuffle instructions with an extra mask arg - #elif SUBGROUP_SHUFFLING_NVIDIA_PRE_VOLTA == 1 || SUBGROUP_SHUFFLING_NVIDIA_POST_VOLTA == 1 - realN ret; - #if SUBGROUP_SHUFFLING_NVIDIA_POST_VOLTA == 1 - asm volatile("shfl.sync.idx.b32 %0, %1, %2, 0x1f, 0xffffffff;" : "=f"(ret): "f"(reg), "r"(src)); - #else - asm volatile("shfl.idx.b32 %0, %1, %2, 0x1f;" : "=f"(ret): "f"(reg), "r"(src)); - #endif - return ret; - #endif -} -#endif // Main body of the matrix-multiplication algorithm. It calls various (inlined) functions. INLINE_FUNC void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK, @@ -838,30 +871,17 @@ INLINE_FUNC void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK, ) { // Allocates workitem-private memory (registers) - #if GEMMK == 0 - #pragma promote_to_registers - realM apm[MWI/VWM]; // MWI * 1 - #pragma promote_to_registers - realN bpm[NWI/VWN]; // 1 * NWI - #elif GEMMK == 1 - #if USE_SUBGROUP_SHUFFLING == 1 - #pragma promote_to_registers - realN apm[KREG/VWN]; // KREG (subgroup shuffling in NWI dimension) - #else - #pragma promote_to_registers - realN apm[NWI*(KREG/VWN)]; // NWI * KREG - #endif - #pragma promote_to_registers - realM bpm[KREG*(MWI/VWM)]; // KREG * MWI - #endif #pragma promote_to_registers - realM cpm[NWI*(MWI/VWM)]; // NWI * MWI + realM apm[MWI/VWM]; // MWI * 1 + #pragma promote_to_registers + realN bpm[NWI/VWN]; // 1 * NWI - #if GEMMK == 1 - const __global real* restrict a_ptr = (const __global real* restrict) &agm[0]; - const __global real* restrict b_ptr = (const __global real* restrict) &bgm[0]; - const int tid_x = get_local_id(0) + MDIMC * GetGroupID0(); - const int tid_y = get_local_id(1) + NDIMC * GetGroupID1(); + #ifdef OUTPUTMN + #pragma promote_to_registers + realN cpn[MWI*(NWI/VWN)]; // MWI * NWI + #else + #pragma promote_to_registers + realM cpm[NWI*(MWI/VWM)]; // NWI * MWI #endif // Combined thread identifier (volatile to disable caching) @@ -870,6 +890,15 @@ INLINE_FUNC void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK, #endif // Initializes the accumulation registers + #ifdef OUTPUTMN + #pragma unroll + for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWI; _mi += 1) { + cpn[_mi * (NWI/VWN) + _ni] = InitAccRegistersN(); + } + } + #else #pragma unroll for (int _mi = 0; _mi < MWI/VWM; _mi += 1) { #pragma unroll @@ -877,6 +906,7 @@ INLINE_FUNC void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK, cpm[_ni * (MWI/VWM) + _mi] = InitAccRegisters(); } } + #endif // Loops over all workgroup tiles for (int kwg = 0; kwg < kSizeK; kwg += KWG * KREG) { @@ -913,147 +943,116 @@ INLINE_FUNC void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK, // Loads data: off-chip --> private (matrix A) #elif GEMMK == 0 && SA == 0 apm[_mi] = GlobalToPrivateA(agm, _mi, kSizeM, idk, kwg); - // Loads data: 2D global --> 2D private (matrix B) - #elif GEMMK == 1 - #pragma unroll - for (int _ki = 0; _ki < KREG; _ki += 1) { - bpm[_ki * (MWI/VWM) + _mi] = GlobalToPrivateB2D(b_ptr, tid_x, _mi, kSizeN, idk, _ki); - } #endif } // Loads matrix B (kernel 0) or matrix A (kernel 1) - #if GEMMK == 0 - #pragma unroll - for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { - // Loads data: local --> private (matrix B) - #if SB == 1 - bpm[_ni] = LocalToPrivateB(blm, _ni, kg); - // Loads data: off-chip --> private (matrix B) - #else - bpm[_ni] = GlobalToPrivateB(bgm, _ni, kSizeN, idk); - #endif - } - #elif GEMMK == 1 - // Loads data: 2D global --> 2D private (matrix A). Partly, shuffled later among subgroups - #if USE_SUBGROUP_SHUFFLING == 1 - const int _ni = clblast_get_sub_group_local_id(); - #pragma unroll - for (int _ki = 0; _ki < KREG/VWN; _ki += 1) { - apm[_ki] = GlobalToPrivateA2D(a_ptr, tid_y, _ni, kSizeK, idk, _ki); - } - // Loads data: 2D global --> 2D private (matrix A) + + #pragma unroll + for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { + // Loads data: local --> private (matrix B) + #if SB == 1 + bpm[_ni] = LocalToPrivateB(blm, _ni, kg); + // Loads data: off-chip --> private (matrix B) #else - #pragma unroll - for (int _ni = 0; _ni < NWI; _ni += 1) { - #pragma unroll - for (int _ki = 0; _ki < KREG/VWN; _ki += 1) { - apm[_ni * (KREG/VWN) + _ki] = GlobalToPrivateA2D(a_ptr, tid_y, _ni, kSizeK, idk, _ki); - } - } + bpm[_ni] = GlobalToPrivateB(bgm, _ni, kSizeN, idk); #endif - #endif + } // Performs the accumulation (Cpm += Apm * Bpm) - #if GEMMK == 0 - #pragma unroll - for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { + + #ifdef OUTPUTMN #pragma unroll for (int _mi = 0; _mi < MWI/VWM; _mi += 1) { - const realM aval = apm[_mi]; - #if VWN == 1 - cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni]); - #elif VWN == 2 - cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni].x); - cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi], aval, bpm[_ni].y); - #elif VWN == 4 - cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni].x); - cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi], aval, bpm[_ni].y); - cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi], aval, bpm[_ni].z); - cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi], aval, bpm[_ni].w); - #elif VWN == 8 - cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni].s0); - cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi], aval, bpm[_ni].s1); - cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi], aval, bpm[_ni].s2); - cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi], aval, bpm[_ni].s3); - cpm[(_ni*VWN + 4)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 4)*(MWI/VWM) + _mi], aval, bpm[_ni].s4); - cpm[(_ni*VWN + 5)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 5)*(MWI/VWM) + _mi], aval, bpm[_ni].s5); - cpm[(_ni*VWN + 6)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 6)*(MWI/VWM) + _mi], aval, bpm[_ni].s6); - cpm[(_ni*VWN + 7)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 7)*(MWI/VWM) + _mi], aval, bpm[_ni].s7); - #elif VWN == 16 - cpm[(_ni*VWN + 0 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0 )*(MWI/VWM) + _mi], aval, bpm[_ni].s0); - cpm[(_ni*VWN + 1 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1 )*(MWI/VWM) + _mi], aval, bpm[_ni].s1); - cpm[(_ni*VWN + 2 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 2 )*(MWI/VWM) + _mi], aval, bpm[_ni].s2); - cpm[(_ni*VWN + 3 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 3 )*(MWI/VWM) + _mi], aval, bpm[_ni].s3); - cpm[(_ni*VWN + 4 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 4 )*(MWI/VWM) + _mi], aval, bpm[_ni].s4); - cpm[(_ni*VWN + 5 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 5 )*(MWI/VWM) + _mi], aval, bpm[_ni].s5); - cpm[(_ni*VWN + 6 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 6 )*(MWI/VWM) + _mi], aval, bpm[_ni].s6); - cpm[(_ni*VWN + 7 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 7 )*(MWI/VWM) + _mi], aval, bpm[_ni].s7); - cpm[(_ni*VWN + 8 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 8 )*(MWI/VWM) + _mi], aval, bpm[_ni].s8); - cpm[(_ni*VWN + 9 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 9 )*(MWI/VWM) + _mi], aval, bpm[_ni].s9); - cpm[(_ni*VWN + 10)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 10)*(MWI/VWM) + _mi], aval, bpm[_ni].sA); - cpm[(_ni*VWN + 11)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 11)*(MWI/VWM) + _mi], aval, bpm[_ni].sB); - cpm[(_ni*VWN + 12)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 12)*(MWI/VWM) + _mi], aval, bpm[_ni].sC); - cpm[(_ni*VWN + 13)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 13)*(MWI/VWM) + _mi], aval, bpm[_ni].sD); - cpm[(_ni*VWN + 14)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 14)*(MWI/VWM) + _mi], aval, bpm[_ni].sE); - cpm[(_ni*VWN + 15)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 15)*(MWI/VWM) + _mi], aval, bpm[_ni].sF); - #endif + #pragma unroll + for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { + const realM aval = apm[_mi]; + #if VWM == 1 + // [MWI/VWM, VWM, NWI/VWN, VWN] + cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni], aval, bpm[_ni]); + #elif VWM == 2 + cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni], aval.x, bpm[_ni]); + cpn[(_mi*VWM + 1)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 1)*(NWI/VWN) + _ni], aval.y, bpm[_ni]); + #elif VWM == 4 + cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni], aval.x, bpm[_ni]); + cpn[(_mi*VWM + 1)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 1)*(NWI/VWN) + _ni], aval.y, bpm[_ni]); + cpn[(_mi*VWM + 2)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 2)*(NWI/VWN) + _ni], aval.z, bpm[_ni]); + cpn[(_mi*VWM + 3)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 3)*(NWI/VWN) + _ni], aval.w, bpm[_ni]); + #elif VWM == 8 + cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 0)*(NWI/VWN) + _ni], aval.s0, bpm[_ni]); + cpn[(_mi*VWM + 1)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 1)*(NWI/VWN) + _ni], aval.s1, bpm[_ni]); + cpn[(_mi*VWM + 2)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 2)*(NWI/VWN) + _ni], aval.s2, bpm[_ni]); + cpn[(_mi*VWM + 3)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 3)*(NWI/VWN) + _ni], aval.s3, bpm[_ni]); + cpn[(_mi*VWM + 4)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 4)*(NWI/VWN) + _ni], aval.s4, bpm[_ni]); + cpn[(_mi*VWM + 5)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 5)*(NWI/VWN) + _ni], aval.s5, bpm[_ni]); + cpn[(_mi*VWM + 6)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 6)*(NWI/VWN) + _ni], aval.s6, bpm[_ni]); + cpn[(_mi*VWM + 7)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 7)*(NWI/VWN) + _ni], aval.s7, bpm[_ni]); + #elif VWM == 16 + cpn[(_mi*VWM + 0 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 0 )*(NWI/VWN) + _ni], aval.s0, bpm[_ni]); + cpn[(_mi*VWM + 1 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 1 )*(NWI/VWN) + _ni], aval.s1, bpm[_ni]); + cpn[(_mi*VWM + 2 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 2 )*(NWI/VWN) + _ni], aval.s2, bpm[_ni]); + cpn[(_mi*VWM + 3 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 3 )*(NWI/VWN) + _ni], aval.s3, bpm[_ni]); + cpn[(_mi*VWM + 4 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 4 )*(NWI/VWN) + _ni], aval.s4, bpm[_ni]); + cpn[(_mi*VWM + 5 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 5 )*(NWI/VWN) + _ni], aval.s5, bpm[_ni]); + cpn[(_mi*VWM + 6 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 6 )*(NWI/VWN) + _ni], aval.s6, bpm[_ni]); + cpn[(_mi*VWM + 7 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 7 )*(NWI/VWN) + _ni], aval.s7, bpm[_ni]); + cpn[(_mi*VWM + 8 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 8 )*(NWI/VWN) + _ni], aval.s8, bpm[_ni]); + cpn[(_mi*VWM + 9 )*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 9 )*(NWI/VWN) + _ni], aval.s9, bpm[_ni]); + cpn[(_mi*VWM + 10)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 10)*(NWI/VWN) + _ni], aval.sA, bpm[_ni]); + cpn[(_mi*VWM + 11)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 11)*(NWI/VWN) + _ni], aval.sB, bpm[_ni]); + cpn[(_mi*VWM + 12)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 12)*(NWI/VWN) + _ni], aval.sC, bpm[_ni]); + cpn[(_mi*VWM + 13)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 13)*(NWI/VWN) + _ni], aval.sD, bpm[_ni]); + cpn[(_mi*VWM + 14)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 14)*(NWI/VWN) + _ni], aval.sE, bpm[_ni]); + cpn[(_mi*VWM + 15)*(NWI/VWN) + _ni] = MultiplyAddVectorN(cpn[(_mi*VWM + 15)*(NWI/VWN) + _ni], aval.sF, bpm[_ni]); + #endif + } } - } - #elif GEMMK == 1 - #pragma unroll - for (int _ni = 0; _ni < NWI; _ni += 1) { + #else #pragma unroll - for (int _mi = 0; _mi < MWI/VWM; _mi += 1) { + for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { #pragma unroll - for (int _ki = 0; _ki < KREG/VWN; _ki += 1) { - #if USE_SUBGROUP_SHUFFLING == 1 - const realN aval = clblast_sub_group_shuffle(apm[_ki], _ni); - #else - const realN aval = apm[_ni * (KREG/VWN) + _ki]; - #endif + for (int _mi = 0; _mi < MWI/VWM; _mi += 1) { + const realM aval = apm[_mi]; #if VWN == 1 - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 0) * (MWI/VWM) + _mi], aval); + cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni]); #elif VWN == 2 - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 0) * (MWI/VWM) + _mi], aval.x); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 1) * (MWI/VWM) + _mi], aval.y); + cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni].x); + cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi], aval, bpm[_ni].y); #elif VWN == 4 - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 0) * (MWI/VWM) + _mi], aval.x); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 1) * (MWI/VWM) + _mi], aval.y); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 2) * (MWI/VWM) + _mi], aval.z); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 3) * (MWI/VWM) + _mi], aval.w); + cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni].x); + cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi], aval, bpm[_ni].y); + cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi], aval, bpm[_ni].z); + cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi], aval, bpm[_ni].w); #elif VWN == 8 - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 0) * (MWI/VWM) + _mi], aval.s0); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 1) * (MWI/VWM) + _mi], aval.s1); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 2) * (MWI/VWM) + _mi], aval.s2); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 3) * (MWI/VWM) + _mi], aval.s3); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 4) * (MWI/VWM) + _mi], aval.s4); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 5) * (MWI/VWM) + _mi], aval.s5); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 6) * (MWI/VWM) + _mi], aval.s6); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 7) * (MWI/VWM) + _mi], aval.s7); + cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0)*(MWI/VWM) + _mi], aval, bpm[_ni].s0); + cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1)*(MWI/VWM) + _mi], aval, bpm[_ni].s1); + cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 2)*(MWI/VWM) + _mi], aval, bpm[_ni].s2); + cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 3)*(MWI/VWM) + _mi], aval, bpm[_ni].s3); + cpm[(_ni*VWN + 4)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 4)*(MWI/VWM) + _mi], aval, bpm[_ni].s4); + cpm[(_ni*VWN + 5)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 5)*(MWI/VWM) + _mi], aval, bpm[_ni].s5); + cpm[(_ni*VWN + 6)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 6)*(MWI/VWM) + _mi], aval, bpm[_ni].s6); + cpm[(_ni*VWN + 7)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 7)*(MWI/VWM) + _mi], aval, bpm[_ni].s7); #elif VWN == 16 - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 0 ) * (MWI/VWM) + _mi], aval.s0); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 1 ) * (MWI/VWM) + _mi], aval.s1); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 2 ) * (MWI/VWM) + _mi], aval.s2); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 3 ) * (MWI/VWM) + _mi], aval.s3); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 4 ) * (MWI/VWM) + _mi], aval.s4); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 5 ) * (MWI/VWM) + _mi], aval.s5); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 6 ) * (MWI/VWM) + _mi], aval.s6); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 7 ) * (MWI/VWM) + _mi], aval.s7); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 8 ) * (MWI/VWM) + _mi], aval.s8); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 9 ) * (MWI/VWM) + _mi], aval.s9); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 10) * (MWI/VWM) + _mi], aval.sA); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 11) * (MWI/VWM) + _mi], aval.sB); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 12) * (MWI/VWM) + _mi], aval.sC); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 13) * (MWI/VWM) + _mi], aval.sD); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 14) * (MWI/VWM) + _mi], aval.sE); - cpm[_ni * (MWI/VWM) + _mi] = MultiplyAddVector(cpm[_ni * (MWI/VWM) + _mi], bpm[(VWN * _ki + 15) * (MWI/VWM) + _mi], aval.sF); + cpm[(_ni*VWN + 0 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 0 )*(MWI/VWM) + _mi], aval, bpm[_ni].s0); + cpm[(_ni*VWN + 1 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 1 )*(MWI/VWM) + _mi], aval, bpm[_ni].s1); + cpm[(_ni*VWN + 2 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 2 )*(MWI/VWM) + _mi], aval, bpm[_ni].s2); + cpm[(_ni*VWN + 3 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 3 )*(MWI/VWM) + _mi], aval, bpm[_ni].s3); + cpm[(_ni*VWN + 4 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 4 )*(MWI/VWM) + _mi], aval, bpm[_ni].s4); + cpm[(_ni*VWN + 5 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 5 )*(MWI/VWM) + _mi], aval, bpm[_ni].s5); + cpm[(_ni*VWN + 6 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 6 )*(MWI/VWM) + _mi], aval, bpm[_ni].s6); + cpm[(_ni*VWN + 7 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 7 )*(MWI/VWM) + _mi], aval, bpm[_ni].s7); + cpm[(_ni*VWN + 8 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 8 )*(MWI/VWM) + _mi], aval, bpm[_ni].s8); + cpm[(_ni*VWN + 9 )*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 9 )*(MWI/VWM) + _mi], aval, bpm[_ni].s9); + cpm[(_ni*VWN + 10)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 10)*(MWI/VWM) + _mi], aval, bpm[_ni].sA); + cpm[(_ni*VWN + 11)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 11)*(MWI/VWM) + _mi], aval, bpm[_ni].sB); + cpm[(_ni*VWN + 12)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 12)*(MWI/VWM) + _mi], aval, bpm[_ni].sC); + cpm[(_ni*VWN + 13)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 13)*(MWI/VWM) + _mi], aval, bpm[_ni].sD); + cpm[(_ni*VWN + 14)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 14)*(MWI/VWM) + _mi], aval, bpm[_ni].sE); + cpm[(_ni*VWN + 15)*(MWI/VWM) + _mi] = MultiplyAddVector(cpm[(_ni*VWN + 15)*(MWI/VWM) + _mi], aval, bpm[_ni].sF); #endif } } - } #endif - } } #if SA == 1 || SB == 1 @@ -1065,46 +1064,30 @@ INLINE_FUNC void XgemmBody(const int kSizeM, const int kSizeN, const int kSizeK, #endif #ifdef OUTPUTMN - // Revise to [M, N] - realN cpn; // MWI * NWI - - real* cpn_mxn = (real *)(&cpn); - real* cpm_nxm = (real *)cpm; - - #pragma unroll - for (int _mi = 0; _mi < MWI; _mi += 1) { - - #pragma unroll - for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { #pragma unroll - for (int _nip = 0; _nip < VWN; _nip += 1) { - cpn_mxn[_nip] = cpm_nxm[(_ni*VWN+_nip) * MWI + _mi]; + for (int _mi = 0; _mi < MWI; _mi += 1) { + #pragma unroll + for (int _ni = 0; _ni < NWI/VWN; _ni += 1) { + StoreResultsN((__global realN* )cgm, cpn[_mi * (NWI/VWN) + _ni], + #ifdef BIAS + egm, + #endif + _mi, _ni, kSizeN, alpha, beta); + } } - - StoreResultsN((__global realN* )cgm, cpn, - #ifdef BIAS - egm, - #endif - _mi, _ni, kSizeN, alpha, beta); - } - } #else - // Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta - #if GEMMK == 0 - const int cld = kSizeM; - #elif GEMMK == 1 - const int cld = kSizeN; - #endif - - #pragma unroll - for (int _ni = 0; _ni < NWI; _ni += 1) { - #pragma unroll - for (int _mi = 0; _mi < MWI/VWM; _mi += 1) { - StoreResultsM(cgm, cpm[_ni * (MWI/VWM) + _mi], _mi, _ni, cld, alpha, beta); - } - } + // Stores an MWG * NWG tile of results and performs the multiplication with alpha and beta + const int cld = kSizeM; + + #pragma unroll + for (int _ni = 0; _ni < NWI; _ni += 1) { + #pragma unroll + for (int _mi = 0; _mi < MWI/VWM; _mi += 1) { + StoreResultsM(cgm, cpm[_ni * (MWI/VWM) + _mi], _mi, _ni, cld, alpha, beta); + } + } #endif } @@ -1123,47 +1106,91 @@ void Xgemm(const int kSizeM, const int kSizeN, const int kSizeK, const __global realN* restrict egm, // [N] #endif __global realM* cgm, - const int a_offset, const int b_offset, const int c_offset) { - const real alpha = GetRealArg(arg_alpha); - const real beta = GetRealArg(arg_beta); - - // Adds the offsets (in case of use of a single temporary buffer for A, B, and C) - agm = (const __global realM*)((const __global real*)agm + a_offset); - bgm = (const __global realN*)((const __global real*)bgm + b_offset); - cgm = (__global realM*)((const __global real*)cgm + c_offset); - - // Allocates workgroup-private memory (local memory) - #if SA == 1 - __local realM alm[KWG * MWG/VWM]; - #endif - #if SB == 1 - __local realN blm[KWG * NWG/VWN]; - #endif + const int a_offset, const int b_offset, const int c_offset +) { + const real alpha = GetRealArg(arg_alpha); + const real beta = GetRealArg(arg_beta); + + // Adds the offsets (in case of use of a single temporary buffer for A, B, and C) + agm = (const __global realM*)((const __global real*)agm + a_offset); + bgm = (const __global realN*)((const __global real*)bgm + b_offset); + cgm = (__global realM*)((const __global real*)cgm + c_offset); + + // Allocates workgroup-private memory (local memory) + #if SA == 1 + __local realM alm[KWG * MWG/VWM]; + #endif + #if SB == 1 + __local realN blm[KWG * NWG/VWN]; + #endif + + // Computes the matrix-multiplication and stores the result in global memory + #if SA == 1 && SB == 1 + XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, + #ifdef BIAS + egm, + #endif + cgm, alpha, beta, alm, blm); + #elif SA == 1 + XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, + #ifdef BIAS + egm, + #endif + cgm, alpha, beta, alm); + #elif SB == 1 + XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, + #ifdef BIAS + egm, + #endif + cgm, alpha, beta, blm); + #else + XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, + #ifdef BIAS + egm, + #endif + cgm, alpha, beta); + #endif +} - // Computes the matrix-multiplication and stores the result in global memory - #if SA == 1 && SB == 1 - XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, - #ifdef BIAS - egm, - #endif - cgm, alpha, beta, alm, blm); - #elif SA == 1 - XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, - #ifdef BIAS - egm, - #endif - cgm, alpha, beta, alm); - #elif SB == 1 - XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, - #ifdef BIAS - egm, - #endif - cgm, alpha, beta, blm); - #else - XgemmBody(kSizeM, kSizeN, kSizeK, agm, bgm, - #ifdef BIAS - egm, - #endif - cgm, alpha, beta); - #endif +#if RELAX_WORKGROUP_SIZE == 1 + __kernel +#else + __kernel __attribute__((reqd_work_group_size(MDIMC, NDIMC, 1))) +#endif +void XgemmBatched(const int kSizeM, const int kSizeN, const int kSizeK, + const real_arg arg_alpha, + const real_arg arg_beta, + const __global realM* restrict agm, const int a_one, const int a_two, + const __global realN* restrict bgm, const int b_one, const int b_two, + __global realM* cgm, const int c_one, const int c_two) { + const int batch = get_group_id(2); + const real alpha = GetRealArg(arg_alpha); + const real beta = GetRealArg(arg_beta); + + // Sets the offsets + const int a_offset = batch * a_one * a_two; + const int b_offset = batch * b_one * b_two; + const int c_offset = batch * c_one * c_two; + const __global realM* restrict agm_ = &agm[a_offset / VWM]; + const __global realN* restrict bgm_ = &bgm[b_offset / VWN]; + __global realM* restrict cgm_ = &cgm[c_offset / VWM]; + + // Allocates workgroup-private memory (local memory) + #if SA == 1 + __local realM alm[KWG * MWG/VWM]; + #endif + #if SB == 1 + __local realN blm[KWG * NWG/VWN]; + #endif + + // Computes the matrix-multiplication and stores the result in global memory + #if SA == 1 && SB == 1 + XgemmBody(kSizeM, kSizeN, kSizeK, agm_, bgm_, cgm_, alpha, beta, alm, blm); + #elif SA == 1 + XgemmBody(kSizeM, kSizeN, kSizeK, agm_, bgm_, cgm_, alpha, beta, alm); + #elif SB == 1 + XgemmBody(kSizeM, kSizeN, kSizeK, agm_, bgm_, cgm_, alpha, beta, blm); + #else + XgemmBody(kSizeM, kSizeN, kSizeK, agm_, bgm_, cgm_, alpha, beta); + #endif } diff --git a/source/backend/opencl/execution/cl/opencl_codegen.py b/source/backend/opencl/execution/cl/opencl_codegen.py index 7082e823c..56d497aee 100644 --- a/source/backend/opencl/execution/cl/opencl_codegen.py +++ b/source/backend/opencl/execution/cl/opencl_codegen.py @@ -1,5 +1,6 @@ import os import sys +import re major_py_ver = sys.version_info.major def convert_string_to_hex_list(code_str): @@ -16,76 +17,85 @@ def opencl_codegen(): if not os.path.exists(cl_kernel_dir): print(cl_kernel_dir + " doesn't exist!") -#common.h - common_header_code = "" -#quantized_common.h - quantized_common_header_code = "" -#activation_common.h - activation_common_header_code = "" - for file_name in os.listdir(cl_kernel_dir): - file_path = os.path.join(cl_kernel_dir, file_name) - if file_path[-2:] == ".h" and file_name[:-2] == "quantized_common": - with open(file_path, "r") as f: - quantized_common_header_code += f.read() - elif file_path[-2:] == ".h" and file_name[:-2] == "activation_common": - with open(file_path, "r") as f: - activation_common_header_code += f.read() - opencl_code_maps = {} - for file_name in os.listdir(cl_kernel_dir): - file_path = os.path.join(cl_kernel_dir, file_name) - if file_path[-3:] == ".cl": - with open(file_path, "r") as f: - code_str = "" - for line in f.readlines(): - if "#include " in line: - code_str += common_header_code - code_str += activation_common_header_code - elif "#include " in line: - code_str += common_header_code - code_str += quantized_common_header_code - elif "#include " in line: - code_str += common_header_code - else: - code_str += line - opencl_code_maps[file_name[:-3]] = convert_string_to_hex_list(code_str) + #source model opencl_source_map = "#include \n" opencl_source_map += "#include \n" opencl_source_map += "#include \n" opencl_source_map += "#include \n" + opencl_source_map += "#include \"opencl_source_map.hpp\" \n" opencl_source_map += "namespace MNN { \n" opencl_source_map += "std::mutex gCLMutex;\n" - opencl_source_map += "extern const std::map> OpenCLProgramMap = \n { \n" + + opencl_source_hpp = "#include \n" + opencl_source_hpp += "#include \n" + opencl_source_hpp += "#include \n" + opencl_source_hpp += "#include \n" + opencl_source_hpp += "namespace MNN { \n" - if major_py_ver == 2: - items = opencl_code_maps.iteritems() - else: - items = opencl_code_maps.items() - for file_name, file_source in items: - if file_name[-4:] == "_buf": - opencl_source_map += "#ifndef MNN_OPENCL_BUFFER_CLOSED\n" - if file_name[-13:] == "_subgroup_buf": - opencl_source_map += "#ifdef MNN_SUPPORT_INTEL_SUBGROUP\n" - opencl_source_map += "{\n \"" - opencl_source_map += file_name - opencl_source_map += "\", \n" - opencl_source_map += " { " - for source_hex in file_source: - opencl_source_map += source_hex - opencl_source_map += "," - opencl_source_map += " } " - opencl_source_map += "\n }, \n" - if file_name[-4:] == "_buf": - opencl_source_map += "#endif\n" - if file_name[-13:] == "_subgroup_buf": - opencl_source_map += "#endif\n" - opencl_source_map += " }; \n" - opencl_source_map += "} \n" + opencl_source_map_hpp = "const std::map OpenCLProgramMap = \n { \n" + spaceReg = re.compile(' +') + for file_name_all in os.listdir(cl_kernel_dir): + file_path = os.path.join(cl_kernel_dir, file_name_all) + if file_path[-3:] == ".cl": + with open(file_path, "r") as f: + file_name = file_name_all[:-3] + if file_name[-4:] == "_buf": + opencl_source_map += "#ifndef MNN_OPENCL_BUFFER_CLOSED\n" + opencl_source_hpp += "#ifndef MNN_OPENCL_BUFFER_CLOSED\n" + opencl_source_map_hpp += "#ifndef MNN_OPENCL_BUFFER_CLOSED\n" + if file_name[-13:] == "_subgroup_buf": + opencl_source_map += "#ifdef MNN_SUPPORT_INTEL_SUBGROUP\n" + opencl_source_hpp += "#ifdef MNN_SUPPORT_INTEL_SUBGROUP\n" + opencl_source_map_hpp += "#ifdef MNN_SUPPORT_INTEL_SUBGROUP\n" + opencl_source_hpp += "extern const char* " + file_name + ";\n" + opencl_source_map += "const char* " + file_name + " = \n" + opencl_source_map_hpp += " { \"" + file_name + "\", " + file_name + " },\n" + lines = f.read().split("\n") + for l in lines: + if (len(l) < 1): + continue + if l.find('printf') >= 0: + l = l.replace('\"', '\\\"') + l = l.replace('\\n', '\\\\n') + opencl_source_map += "\""+l+"\"\n" + elif l.find('\\') >= 0: + l = l.replace('\\', '') + l = spaceReg.sub(' ', l) + opencl_source_map += "\""+l+"\"" + else: + l = l + "\\n" + l = l.replace('\t', '') + l = spaceReg.sub(' ', l) + l = l.replace(', ', ',') + l = l.replace(' = ', '=') + l = l.replace(' + ', '+') + l = l.replace(' - ', '-') + l = l.replace(' * ', '*') + l = l.replace(' / ', '/') + l = l.replace(' < ', '<') + l = l.replace(' > ', '>') + opencl_source_map += "\""+l+"\"\n" + opencl_source_map += ";\n" + if file_name[-4:] == "_buf": + opencl_source_map += "#endif\n" + opencl_source_hpp += "#endif\n" + opencl_source_map_hpp += "#endif\n" + if file_name[-13:] == "_subgroup_buf": + opencl_source_map += "#endif\n" + opencl_source_hpp += "#endif\n" + opencl_source_map_hpp += "#endif\n" + opencl_source_map += "}\n" + opencl_source_map_hpp += "};\n" + opencl_source_map_hpp += "}\n" with open(output_path, "w") as w_file: w_file.write(opencl_source_map) + with open("opencl_source_map.hpp", "w") as w_file: + w_file.write(opencl_source_hpp) + w_file.write(opencl_source_map_hpp) print("Generate OpenCL Source done !!! \n") diff --git a/source/backend/opencl/execution/cl/opencl_program.cc b/source/backend/opencl/execution/cl/opencl_program.cc index 7a460a3a0..b72288012 100644 --- a/source/backend/opencl/execution/cl/opencl_program.cc +++ b/source/backend/opencl/execution/cl/opencl_program.cc @@ -2,357 +2,22626 @@ #include #include #include +#include "opencl_source_map.hpp" namespace MNN { std::mutex gCLMutex; -extern const std::map> OpenCLProgramMap = - { -{ - "conv_2d", - { 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} - }, -#ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "grid_sample_buf", - { 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} - }, -#ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "range_buf", - { 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} - }, -#ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "gemv_conv1x1_buf", - { 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} - }, +const char* conv_2d = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define READ_INPUT_IMAGE(i, base) "" int in_width_value##i = in_width##i + base; "" in_width_value##i = "" select(in_idx + in_width_value##i, -1, (in_width_value##i < 0 || in_width_value##i >= input_shape.y)); "" in##i=RI_F(input,SAMPLER,(int2)(in_width_value##i,in_hb_value));\n" +"#define CALCULATE_OUTPUT(i) "" out##i = mad(in##i.x, weights0, out##i); "" out##i = mad(in##i.y, weights1, out##i); "" out##i = mad(in##i.z, weights2, out##i); "" out##i=mad(in##i.w,weights3,out##i); \n" +"#define CALCULATE_OUTPUT_WEIGHTS4(i, j) "" out##i = mad(in##j.x, weights4, out##i); "" out##i = mad(in##j.y, weights5, out##i); "" out##i = mad(in##j.z, weights6, out##i); "" out##i=mad(in##j.w,weights7,out##i);\n" +"#define CALCULATE_OUTPUT_OPT(i) "" out##i = mad(in_sm##i[local_idx].x, weights0, out##i); "" out##i = mad(in_sm##i[local_idx].y, weights1, out##i); "" out##i = mad(in_sm##i[local_idx].z, weights2, out##i); "" out##i=mad(in_sm##i[local_idx].w,weights3,out##i); \n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"#define UNIT 4\n" +"#define MOD_NUM 15\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" #define PADZEROSVEC(k, channel, data0, data1, data2, data3) "" data0 = (k << 2) < channel ? data0 : 0; "" data1 = (k << 2) + 1 < channel ? data1 : 0; "" data2 = (k << 2) + 2 < channel ? data2 : 0; "" data3=(k << 2)+3= 4) {\n" +" WI_F(output,(int2)(output_idx,out_b_h_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,out_b_h_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,out_b_h_idx),out2);\n" +" WI_F(output,(int2)(output_idx+3,out_b_h_idx),out3);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(output_idx,out_b_h_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,out_b_h_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,out_b_h_idx),out2);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(output_idx,out_b_h_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,out_b_h_idx),out1);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(output_idx,out_b_h_idx),out0);\n" +" }\n" +"}\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void conv_2d_1x1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_BUFFER)\n" +" __global const FLOAT *weights,\n" +"#else\n" +" __read_only image2d_t weights,\n" +"#endif\n" +" __read_only image2d_t bias,\n" +" __write_only image2d_t output,\n" +" __private const int2 input_shape,\n" +" __private const int in_channel_block,__private const int2 output_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int output_width_4,\n" +" __private const int out_channel_blocks\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" ,__private const int blockDim\n" +" ,__private const int inChannel\n" +"#endif\n" +") {\n" +" const int output_channel_width_idx=get_global_id(0);\n" +" const int output_batch_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(output_channel_width_idx,output_batch_height_idx);\n" +" const int output_channel_block_idx=output_channel_width_idx/output_width_4;\n" +" const int output_width_block_idx=output_channel_width_idx % output_width_4;\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" int weight_ic_offset=output_channel_block_idx*8;\n" +" int weight_oc_offset=out_channel_blocks*8;\n" +"#else\n" +" int weight_ic_offset=output_channel_block_idx*16;\n" +" int weight_oc_offset=out_channel_blocks*16;\n" +"#endif\n" +" FLOAT4 out0=RI_F(bias,SAMPLER,(int2)(output_channel_block_idx,0));\n" +" FLOAT4 out1=out0;\n" +" FLOAT4 out2=out0;\n" +" FLOAT4 out3=out0;\n" +"#ifdef MNN_CONV_S1D1\n" +" int intput_width_idx0=output_width_block_idx << 2;\n" +" int intput_width_idx1=intput_width_idx0+1;\n" +" int intput_width_idx2=intput_width_idx0+2;\n" +" int intput_width_idx3=intput_width_idx0+3;\n" +"#else\n" +" int intput_width_idx0=mul24(output_width_block_idx,stride_shape.y*4);\n" +" int intput_width_idx1=intput_width_idx0+stride_shape.y;\n" +" int intput_width_idx2=intput_width_idx1+stride_shape.y;\n" +" int intput_width_idx3=intput_width_idx2+stride_shape.y;\n" +" intput_width_idx0=select(intput_width_idx0,INT_MIN,intput_width_idx0 >= input_shape.y);\n" +" intput_width_idx1=select(intput_width_idx1,INT_MIN,intput_width_idx1 >= input_shape.y);\n" +" intput_width_idx2=select(intput_width_idx2,INT_MIN,intput_width_idx2 >= input_shape.y);\n" +" intput_width_idx3=select(intput_width_idx3,INT_MIN,intput_width_idx3 >= input_shape.y);\n" +"#endif\n" +" int batch_index=output_batch_height_idx/output_shape.x;\n" +" int input_height_block_idx=mul24((output_batch_height_idx % output_shape.x),stride_shape.x)+batch_index*input_shape.x;\n" +" FLOAT4 in0;\n" +" FLOAT4 in1;\n" +" FLOAT4 in2;\n" +" FLOAT4 in3;\n" +" FLOAT4 weights0;\n" +" FLOAT4 weights1;\n" +" FLOAT4 weights2;\n" +" FLOAT4 weights3;\n" +" int weight_offset=output_channel_block_idx*in_channel_block*4*4;\n" +" for (int in_channel_block_idx=0; in_channel_block_idx> 4)-8;\n" +" charWeights0.y=(charWeightsInt4.s0 & MOD_NUM)-8;\n" +" charWeights0.z=(charWeightsInt4.s1 >> 4)-8;\n" +" charWeights0.w=(charWeightsInt4.s1 & MOD_NUM)-8;\n" +" charWeights1.x=(charWeightsInt4.s2 >> 4)-8;\n" +" charWeights1.y=(charWeightsInt4.s2 & MOD_NUM)-8;\n" +" charWeights1.z=(charWeightsInt4.s3 >> 4)-8;\n" +" charWeights1.w=(charWeightsInt4.s3 & MOD_NUM)- 8;\n" +" charWeights2.x=(charWeightsInt4.s4 >> 4)-8;\n" +" charWeights2.y=(charWeightsInt4.s4 & MOD_NUM)-8;\n" +" charWeights2.z=(charWeightsInt4.s5 >> 4)-8;\n" +" charWeights2.w=(charWeightsInt4.s5 & MOD_NUM)-8;\n" +" charWeights3.x=(charWeightsInt4.s6 >> 4)-8;\n" +" charWeights3.y=(charWeightsInt4.s6 & MOD_NUM)-8;\n" +" charWeights3.z=(charWeightsInt4.s7 >> 4)-8;\n" +" charWeights3.w=(charWeightsInt4.s7 & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeights0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeights1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeights2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeights3),scale0,offset0);\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(weights_width_base,weights+weight_offset);\n" +" weights1=vload4(weights_width_base+1,weights+weight_offset);\n" +" weights2=vload4(weights_width_base+2,weights+weight_offset);\n" +" weights3=vload4(weights_width_base+3,weights+weight_offset);\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_width_base+0,output_channel_block_idx));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_width_base+1,output_channel_block_idx));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_width_base+2,output_channel_block_idx));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_width_base+3,output_channel_block_idx));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" in0=RI_F(input,SAMPLER,(int2)(input_width_base+intput_width_idx0,input_height_block_idx));\n" +" in1=RI_F(input,SAMPLER,(int2)(input_width_base+intput_width_idx1,input_height_block_idx));\n" +" in2=RI_F(input,SAMPLER,(int2)(input_width_base+intput_width_idx2,input_height_block_idx));\n" +" in3=RI_F(input,SAMPLER,(int2)(input_width_base+intput_width_idx3,input_height_block_idx));\n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +" out1=fmax(out1,(FLOAT4)0);\n" +" out2=fmax(out2,(FLOAT4)0);\n" +" out3=fmax(out3,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +" out1=clamp(out1,(FLOAT4)0,(FLOAT4)6);\n" +" out2=clamp(out2,(FLOAT4)0,(FLOAT4)6);\n" +" out3=clamp(out3,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" const int out_x_base=mul24(output_channel_block_idx,output_shape.y);\n" +" int out_x_idx=output_width_block_idx << 2;\n" +" const int remain=output_shape.y-out_x_idx;\n" +" int output_idx=out_x_base+out_x_idx;\n" +" if (remain >= 4) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out2);\n" +" WI_F(output,(int2)(output_idx+3,output_batch_height_idx),out3);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out2);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" }\n" +"}\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_BUFFER)\n" +" __global const FLOAT *weights,\n" +"#else\n" +" __read_only image2d_t weights,\n" +"#endif\n" +" __read_only image2d_t bias,\n" +" __write_only image2d_t output,\n" +" __private const int2 input_shape,\n" +" __private const int in_channel_block,__private const int2 output_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int output_width_4,\n" +" __private const int out_channel_blocks\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" ,__private const int blockDim\n" +" ,__private const int inChannel\n" +"#endif\n" +") {\n" +" const int output_channel_width_idx=get_global_id(0);\n" +" const int output_batch_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(output_channel_width_idx,output_batch_height_idx);\n" +" const int output_channel_block_idx=output_channel_width_idx/output_width_4;\n" +" const int output_width_block_idx=output_channel_width_idx % output_width_4;\n" +" const int output_channel_idx=output_channel_block_idx << 1;\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" int weight_ic_offset=output_channel_block_idx*16;\n" +" int weight_oc_offset=out_channel_blocks*8;\n" +"#else\n" +" int weight_ic_offset=output_channel_block_idx*32;\n" +" int weight_oc_offset=out_channel_blocks*16;\n" +"#endif\n" +" FLOAT4 out0=RI_F(bias,SAMPLER,(int2)(output_channel_idx,0));\n" +" FLOAT4 out1=out0;\n" +" FLOAT4 out2=out0;\n" +" FLOAT4 out3=out0;\n" +" \n" +" FLOAT4 out4=RI_F(bias,SAMPLER,(int2)(output_channel_idx+1,0));\n" +" FLOAT4 out5=out4;\n" +" FLOAT4 out6=out4;\n" +" FLOAT4 out7=out4;\n" +"#ifdef MNN_CONV_S1D1\n" +" int intput_width_idx0=output_width_block_idx << 2;\n" +" int intput_width_idx1=intput_width_idx0+1;\n" +" int intput_width_idx2=intput_width_idx0+2;\n" +" int intput_width_idx3=intput_width_idx0+3;\n" +"#else\n" +" int intput_width_idx0=mul24(output_width_block_idx,stride_shape.y*4);\n" +" int intput_width_idx1=intput_width_idx0+stride_shape.y;\n" +" int intput_width_idx2=intput_width_idx1+stride_shape.y;\n" +" int intput_width_idx3=intput_width_idx2+stride_shape.y;\n" +" intput_width_idx0=select(intput_width_idx0,INT_MIN,intput_width_idx0 >= input_shape.y);\n" +" intput_width_idx1=select(intput_width_idx1,INT_MIN,intput_width_idx1 >= input_shape.y);\n" +" intput_width_idx2=select(intput_width_idx2,INT_MIN,intput_width_idx2 >= input_shape.y);\n" +" intput_width_idx3=select(intput_width_idx3,INT_MIN,intput_width_idx3 >= input_shape.y);\n" +"#endif\n" +" int batch_index=output_batch_height_idx/output_shape.x;\n" +" int input_height_block_idx=mul24((output_batch_height_idx % output_shape.x),stride_shape.x)+batch_index*input_shape.x;\n" +" FLOAT4 in0;\n" +" FLOAT4 in1;\n" +" FLOAT4 in2;\n" +" FLOAT4 in3;\n" +" FLOAT4 weights0;\n" +" FLOAT4 weights1;\n" +" FLOAT4 weights2;\n" +" FLOAT4 weights3;\n" +" FLOAT4 weights4;\n" +" FLOAT4 weights5;\n" +" FLOAT4 weights6;\n" +" FLOAT4 weights7;\n" +" int weight_offset=output_channel_idx*in_channel_block*4*4;\n" +" int weight_offset1=weight_offset+in_channel_block*4*4;\n" +" for (int in_channel_block_idx=0; in_channel_block_idx> 4)-8;\n" +" charWeights0.y=(charWeightsInt4.s0 & MOD_NUM)-8;\n" +" charWeights0.z=(charWeightsInt4.s1 >> 4)-8;\n" +" charWeights0.w=(charWeightsInt4.s1 & MOD_NUM)-8;\n" +" charWeights1.x=(charWeightsInt4.s2 >> 4)-8;\n" +" charWeights1.y=(charWeightsInt4.s2 & MOD_NUM)-8;\n" +" charWeights1.z=(charWeightsInt4.s3 >> 4)-8;\n" +" charWeights1.w=(charWeightsInt4.s3 & MOD_NUM)-8;\n" +" charWeights2.x=(charWeightsInt4.s4 >> 4)-8;\n" +" charWeights2.y=(charWeightsInt4.s4 & MOD_NUM)-8;\n" +" charWeights2.z=(charWeightsInt4.s5 >> 4)-8;\n" +" charWeights2.w=(charWeightsInt4.s5 & MOD_NUM)-8;\n" +" charWeights3.x=(charWeightsInt4.s6 >> 4)-8;\n" +" charWeights3.y=(charWeightsInt4.s6 & MOD_NUM)-8;\n" +" charWeights3.z=(charWeightsInt4.s7 >> 4)-8;\n" +" charWeights3.w=(charWeightsInt4.s7 & MOD_NUM)-8;\n" +" charWeights4.x=(charWeightsInt4.s8 >> 4)-8;\n" +" charWeights4.y=(charWeightsInt4.s8 & MOD_NUM)-8;\n" +" charWeights4.z=(charWeightsInt4.s9 >> 4)-8;\n" +" charWeights4.w=(charWeightsInt4.s9 & MOD_NUM)-8;\n" +" charWeights5.x=(charWeightsInt4.sa >> 4)-8;\n" +" charWeights5.y=(charWeightsInt4.sa & MOD_NUM)-8;\n" +" charWeights5.z=(charWeightsInt4.sb >> 4)-8;\n" +" charWeights5.w=(charWeightsInt4.sb & MOD_NUM)-8;\n" +" charWeights6.x=(charWeightsInt4.sc >> 4)-8;\n" +" charWeights6.y=(charWeightsInt4.sc & MOD_NUM)-8;\n" +" charWeights6.z=(charWeightsInt4.sd >> 4)-8;\n" +" charWeights6.w=(charWeightsInt4.sd & MOD_NUM)-8;\n" +" charWeights7.x=(charWeightsInt4.se >> 4)-8;\n" +" charWeights7.y=(charWeightsInt4.se & MOD_NUM)-8;\n" +" charWeights7.z=(charWeightsInt4.sf >> 4)-8;\n" +" charWeights7.w=(charWeightsInt4.sf & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeights0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeights1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeights2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeights3),scale0,offset0);\n" +" weights4=mad(CONVERT_FLOAT4(charWeights4),scale1,offset1);\n" +" weights5=mad(CONVERT_FLOAT4(charWeights5),scale1,offset1);\n" +" weights6=mad(CONVERT_FLOAT4(charWeights6),scale1,offset1);\n" +" weights7=mad(CONVERT_FLOAT4(charWeights7),scale1,offset1);\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(weights_width_base,weights+weight_offset);\n" +" weights1=vload4(weights_width_base+1,weights+weight_offset);\n" +" weights2=vload4(weights_width_base+2,weights+weight_offset);\n" +" weights3=vload4(weights_width_base+3,weights+weight_offset);\n" +" weights4=vload4(weights_width_base,weights+weight_offset1);\n" +" weights5=vload4(weights_width_base+1,weights+weight_offset1);\n" +" weights6=vload4(weights_width_base+2,weights+weight_offset1);\n" +" weights7=vload4(weights_width_base+3,weights+weight_offset1);\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_width_base+0,output_channel_idx));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_width_base+1,output_channel_idx));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_width_base+2,output_channel_idx));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_width_base+3,output_channel_idx));\n" +" \n" +" weights4=RI_F(weights,SAMPLER,(int2)(weights_width_base+0,output_channel_idx+1));\n" +" weights5=RI_F(weights,SAMPLER,(int2)(weights_width_base+1,output_channel_idx+1));\n" +" weights6=RI_F(weights,SAMPLER,(int2)(weights_width_base+2,output_channel_idx+1));\n" +" weights7=RI_F(weights,SAMPLER,(int2)(weights_width_base+3,output_channel_idx+1));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights4,weights5,weights6,weights7);\n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" \n" +" CALCULATE_OUTPUT_WEIGHTS4(4,0);\n" +" CALCULATE_OUTPUT_WEIGHTS4(5,1);\n" +" CALCULATE_OUTPUT_WEIGHTS4(6,2);\n" +" CALCULATE_OUTPUT_WEIGHTS4(7,3);\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +" out1=fmax(out1,(FLOAT4)0);\n" +" out2=fmax(out2,(FLOAT4)0);\n" +" out3=fmax(out3,(FLOAT4)0);\n" +" out4=fmax(out4,(FLOAT4)0);\n" +" out5=fmax(out5,(FLOAT4)0);\n" +" out6=fmax(out6,(FLOAT4)0);\n" +" out7=fmax(out7,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +" out1=clamp(out1,(FLOAT4)0,(FLOAT4)6);\n" +" out2=clamp(out2,(FLOAT4)0,(FLOAT4)6);\n" +" out3=clamp(out3,(FLOAT4)0,(FLOAT4)6);\n" +" out4=clamp(out4,(FLOAT4)0,(FLOAT4)6);\n" +" out5=clamp(out5,(FLOAT4)0,(FLOAT4)6);\n" +" out6=clamp(out6,(FLOAT4)0,(FLOAT4)6);\n" +" out7=clamp(out7,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" const int out_x_base=mul24(output_channel_idx,output_shape.y);\n" +" int out_x_idx=output_width_block_idx << 2;\n" +" const int remain=output_shape.y-out_x_idx;\n" +" int output_idx=out_x_base+out_x_idx;\n" +" if (remain >= 4) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out2);\n" +" WI_F(output,(int2)(output_idx+3,output_batch_height_idx),out3);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out2);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" }\n" +" \n" +" if(output_channel_idx+1 >= out_channel_blocks)\n" +" return;\n" +" output_idx += output_shape.y;\n" +" if (remain >= 4) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out4);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out5);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out6);\n" +" WI_F(output,(int2)(output_idx+3,output_batch_height_idx),out7);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out4);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out5);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out6);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out4);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out5);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out4);\n" +" }\n" +"}\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_BUFFER)\n" +" __global const FLOAT *weights,\n" +"#else\n" +" __read_only image2d_t weights,\n" +"#endif\n" +"#ifdef BIAS\n" +" __read_only image2d_t bias,\n" +"#endif\n" +" __write_only image2d_t output,\n" +" __private const int2 input_shape,\n" +" __private const int in_channel_block_length,\n" +" __private const int2 output_shape,\n" +" __private const int2 weights_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 padding_shape,\n" +" __private const int2 dilation_shape,\n" +" __private const int out_width_blocks,\n" +" __private const int out_channel_blocks,\n" +" __private const int out_height_blocks\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" ,__private const int blockDim\n" +" ,__private const int inChannel\n" +"#endif\n" +") {\n" +" const int output_channel_width_idx=get_global_id(0);\n" +" const int output_batch_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(output_channel_width_idx,output_batch_height_idx);\n" +" const int out_channel_block_idx=output_channel_width_idx/out_width_blocks;\n" +" const int out_height_block_idx=output_channel_width_idx % out_width_blocks;\n" +"#ifdef BIAS\n" +" FLOAT4 out0=RI_F(bias,SAMPLER,(int2)(out_channel_block_idx,0));\n" +"#else\n" +" FLOAT4 out0=(FLOAT4)0;\n" +"#endif\n" +" FLOAT4 out1=out0;\n" +" FLOAT4 out2=out0;\n" +" FLOAT4 out3=out0;\n" +" int in_width0=mad24(out_height_block_idx,stride_shape.y<<2,-padding_shape.y);\n" +" int in_width1=in_width0+stride_shape.y;\n" +" int in_width2=in_width0+stride_shape.y*2;\n" +" int in_width3=in_width0+stride_shape.y*3;\n" +" \n" +"#ifdef MNN_CONV_S1D1\n" +" const int height_start=mad24((output_batch_height_idx % output_shape.x),1,-padding_shape.x);\n" +" const int kh_start=select(0,(-height_start),height_start<0);\n" +" int in_height_start=kh_start+height_start;\n" +" int in_height_end=min(weights_shape.x+height_start,input_shape.x);\n" +" const int batch_idx=mul24((output_batch_height_idx/output_shape.x),input_shape.x);\n" +" const int weights_h_idx=mul24(out_channel_block_idx,mul24(weights_shape.y,weights_shape.x))+mul24(select(0,(-height_start),height_start<0),weights_shape.y);\n" +"#else\n" +" const int height_start=mad24((output_batch_height_idx % output_shape.x),stride_shape.x,-padding_shape.x);\n" +" const int kh_start=select(0,(-height_start+dilation_shape.x-1)/dilation_shape.x,height_start<0);\n" +" int in_height_start=mad24(kh_start,dilation_shape.x,height_start);\n" +" int in_height_end=min(mad24(weights_shape.x,dilation_shape.x,height_start),input_shape.x);\n" +" const int batch_idx=mul24((output_batch_height_idx/output_shape.x),input_shape.x);\n" +" const int weights_h_idx=mul24(out_channel_block_idx,mul24(weights_shape.y,weights_shape.x))+mul24(select(0,(-height_start+dilation_shape.x-1)/dilation_shape.x,height_start<0),weights_shape.y);\n" +"#endif\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER)\n" +" const int weight_oc_offset=out_channel_blocks*weights_shape.x*weights_shape.y*4;\n" +"#endif\n" +" FLOAT4 in0,in1,in2,in3;\n" +" FLOAT4 weights0,weights1,weights2,weights3;\n" +" for (int in_channel_block_idx=0; in_channel_block_idx> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" weight_offset += 4;\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(0,weights+weight_offset);\n" +" weights1=vload4(0,weights+weight_offset+weight_oc_offset);\n" +" weights2=vload4(0,weights+weight_offset+weight_oc_offset*2);\n" +" weights3=vload4(0,weights+weight_offset+weight_oc_offset*3);\n" +" weight_offset += 4;\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_x_idx+0,weights_y_idx));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_x_idx+1,weights_y_idx));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_x_idx+2,weights_y_idx));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_x_idx+3,weights_y_idx++));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" }\n" +" for (int w=1; w> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" weight_offset += 4;\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(0,weights+weight_offset);\n" +" weights1=vload4(0,weights+weight_offset+weight_oc_offset);\n" +" weights2=vload4(0,weights+weight_offset+weight_oc_offset*2);\n" +" weights3=vload4(0,weights+weight_offset+weight_oc_offset*3);\n" +" weight_offset += 4;\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_x_idx+0,weights_y_idx));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_x_idx+1,weights_y_idx));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_x_idx+2,weights_y_idx));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_x_idx+3,weights_y_idx++));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" }\n" +"#else\n" +" for (int w=0; w> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" weight_offset += 4;\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(0,weights+weight_offset);\n" +" weights1=vload4(0,weights+weight_offset+weight_oc_offset);\n" +" weights2=vload4(0,weights+weight_offset+weight_oc_offset*2);\n" +" weights3=vload4(0,weights+weight_offset+weight_oc_offset*3);\n" +" weight_offset += 4;\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_x_idx+0,weights_y_idx)); \n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_x_idx+1,weights_y_idx)); \n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_x_idx+2,weights_y_idx)); \n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_x_idx+3,weights_y_idx++));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" }\n" +"#endif\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +" out1=fmax(out1,(FLOAT4)0);\n" +" out2=fmax(out2,(FLOAT4)0);\n" +" out3=fmax(out3,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +" out1=clamp(out1,(FLOAT4)0,(FLOAT4)6);\n" +" out2=clamp(out2,(FLOAT4)0,(FLOAT4)6);\n" +" out3=clamp(out3,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" const int out_x_base=mul24(out_channel_block_idx,output_shape.y);\n" +" int out_x_idx=out_height_block_idx << 2;\n" +" const int remain=output_shape.y-out_x_idx;\n" +" int output_idx=out_x_base+out_x_idx;\n" +" if (remain >= 4) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out2);\n" +" WI_F(output,(int2)(output_idx+3,output_batch_height_idx),out3);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" WI_F(output,(int2)(output_idx+2,output_batch_height_idx),out2);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" WI_F(output,(int2)(output_idx+1,output_batch_height_idx),out1);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(output_idx,output_batch_height_idx),out0);\n" +" }\n" +"}\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_BUFFER)\n" +" __global const FLOAT *weights,\n" +"#else\n" +" __read_only image2d_t weights,\n" +"#endif\n" +"#ifdef BIAS\n" +" __read_only image2d_t bias,\n" +"#endif\n" +" __write_only image2d_t output,\n" +" __private const int2 input_shape,\n" +" __private const int in_channel_block_length,\n" +" __private const int2 output_shape,\n" +" __private const int2 weights_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 padding_shape,\n" +" __private const int2 dilation_shape,\n" +" __private const int out_width_blocks,\n" +" __private const int out_channel_blocks,\n" +" __private const int out_height_blocks\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" ,__private const int blockDim\n" +" ,__private const int inChannel\n" +"#endif\n" +") {\n" +" const int output_channel_width_idx=get_global_id(0);\n" +" const int output_batch_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(output_channel_width_idx,output_batch_height_idx);\n" +" const int out_channel_block_idx=(output_channel_width_idx/out_width_blocks) << 1;\n" +" const int out_width_block_idx=output_channel_width_idx % out_width_blocks;\n" +" const int out_height_block_idx=(output_batch_height_idx % out_height_blocks);\n" +" const int out_batch_block_idx=output_batch_height_idx/out_height_blocks;\n" +"#ifdef BIAS\n" +" FLOAT4 out0=RI_F(bias,SAMPLER,(int2)(out_channel_block_idx,0));\n" +" FLOAT4 out4=RI_F(bias,SAMPLER,(int2)(out_channel_block_idx+1,0));\n" +"#else\n" +" FLOAT4 out0=(FLOAT4)0;\n" +" FLOAT4 out4=(FLOAT4)0;\n" +"#endif\n" +" FLOAT4 out1=out0;\n" +" FLOAT4 out2=out0;\n" +" FLOAT4 out3=out0;\n" +" FLOAT4 out5=out4;\n" +" FLOAT4 out6=out4;\n" +" FLOAT4 out7=out4;\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER)\n" +" const int weight_oc_offset=weights_shape.x*weights_shape.y*4;\n" +" const int weight_ic_offset=out_channel_blocks*weight_oc_offset;\n" +"#endif\n" +" int in_width0=mad24(out_width_block_idx,stride_shape.y,-padding_shape.y);\n" +" int in_height0=mad24(out_height_block_idx,stride_shape.x<<2,-padding_shape.x);\n" +" int in_height1=in_height0+stride_shape.x;\n" +" int in_height2=in_height1+stride_shape.x;\n" +" int in_height3=in_height2+stride_shape.x;\n" +" int weight_size=mul24(weights_shape.y,weights_shape.x);\n" +" \n" +" const int weights_h_idx=mul24(out_channel_block_idx,weight_size);\n" +" const int batch_idx=mul24(out_batch_block_idx,input_shape.x);\n" +" \n" +" FLOAT4 in0,in1,in2,in3;\n" +" FLOAT4 weights0,weights1,weights2,weights3,weights4,weights5,weights6,weights7;\n" +" for (int in_channel_block_idx=0; in_channel_block_idx= input_shape.x));\n" +" int h1=select(in_height1+iy+batch_idx,-1,(in_height1+iy<0 || in_height1+iy >= input_shape.x));\n" +" int h2=select(in_height2+iy+batch_idx,-1,(in_height2+iy<0 || in_height2+iy >= input_shape.x));\n" +" int h3=select(in_height3+iy+batch_idx,-1,(in_height3+iy<0 || in_height3+iy >= input_shape.x));\n" +" for (int ix=0; ix= input_shape.y));\n" +" \n" +" in0=RI_F(input,SAMPLER,(int2)(w0,h0));\n" +" in1=RI_F(input,SAMPLER,(int2)(w0,h1));\n" +" in2=RI_F(input,SAMPLER,(int2)(w0,h2));\n" +" in3=RI_F(input,SAMPLER,(int2)(w0,h3));\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,kernel_ptr+weight_offset);\n" +" char4 charWeight1=vload4(0,kernel_ptr+weight_offset+weight_ic_offset);\n" +" char4 charWeight2=vload4(0,kernel_ptr+weight_offset+weight_ic_offset*2);\n" +" char4 charWeight3=vload4(0,kernel_ptr+weight_offset+weight_ic_offset*3);\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" charWeight0=vload4(0,kernel_ptr+weight_offset+weight_oc_offset);\n" +" charWeight1=vload4(0,kernel_ptr+weight_offset+weight_oc_offset+weight_ic_offset);\n" +" charWeight2=vload4(0,kernel_ptr+weight_offset+weight_oc_offset+weight_ic_offset*2);\n" +" charWeight3=vload4(0,kernel_ptr+weight_offset+weight_oc_offset+weight_ic_offset*3);\n" +" weights4=mad(CONVERT_FLOAT4(charWeight0),scale1,offset1);\n" +" weights5=mad(CONVERT_FLOAT4(charWeight1),scale1,offset1);\n" +" weights6=mad(CONVERT_FLOAT4(charWeight2),scale1,offset1);\n" +" weights7=mad(CONVERT_FLOAT4(charWeight3),scale1,offset1);\n" +" weight_offset += 4;\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" uchar2 charWeightInt40=vload2(0,kernel_ptr+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,kernel_ptr+weight_offset/2+weight_ic_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,kernel_ptr+weight_offset/2+weight_ic_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,kernel_ptr+weight_offset/2+weight_ic_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)- 8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" charWeightInt40=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset/2);\n" +" charWeightInt41=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2);\n" +" charWeightInt42=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset/2+weight_ic_offset*2/2);\n" +" charWeightInt43=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset/2+weight_ic_offset*3/2);\n" +" charWeight0=(char4)(0,0,0,0);\n" +" charWeight1=(char4)(0,0,0,0);\n" +" charWeight2=(char4)(0,0,0,0);\n" +" charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)- 8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)- 8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weights4=mad(CONVERT_FLOAT4(charWeight0),scale1,offset1);\n" +" weights5=mad(CONVERT_FLOAT4(charWeight1),scale1,offset1);\n" +" weights6=mad(CONVERT_FLOAT4(charWeight2),scale1,offset1);\n" +" weights7=mad(CONVERT_FLOAT4(charWeight3),scale1,offset1);\n" +" weight_offset += 4;\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(0,weights+weight_offset);\n" +" weights1=vload4(0,weights+weight_offset+weight_ic_offset);\n" +" weights2=vload4(0,weights+weight_offset+weight_ic_offset*2);\n" +" weights3=vload4(0,weights+weight_offset+weight_ic_offset*3);\n" +" weights4=vload4(0,weights+weight_offset+weight_oc_offset);\n" +" weights5=vload4(0,weights+weight_offset+weight_ic_offset+weight_oc_offset);\n" +" weights6=vload4(0,weights+weight_offset+weight_ic_offset*2+weight_oc_offset);\n" +" weights7=vload4(0,weights+weight_offset+weight_ic_offset*3+weight_oc_offset);\n" +" weight_offset += 4;\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_x_idx+0,weights_y_idx));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_x_idx+1,weights_y_idx));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_x_idx+2,weights_y_idx));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_x_idx+3,weights_y_idx));\n" +" weights4=RI_F(weights,SAMPLER,(int2)(weights_x_idx+0,weight_size+weights_y_idx));\n" +" weights5=RI_F(weights,SAMPLER,(int2)(weights_x_idx+1,weight_size+weights_y_idx));\n" +" weights6=RI_F(weights,SAMPLER,(int2)(weights_x_idx+2,weight_size+weights_y_idx));\n" +" weights7=RI_F(weights,SAMPLER,(int2)(weights_x_idx+3,weight_size+weights_y_idx++));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights4,weights5,weights6,weights7);\n" +" \n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" CALCULATE_OUTPUT_WEIGHTS4(4,0);\n" +" CALCULATE_OUTPUT_WEIGHTS4(5,1);\n" +" CALCULATE_OUTPUT_WEIGHTS4(6,2);\n" +" CALCULATE_OUTPUT_WEIGHTS4(7,3);\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +" out1=fmax(out1,(FLOAT4)0);\n" +" out2=fmax(out2,(FLOAT4)0);\n" +" out3=fmax(out3,(FLOAT4)0);\n" +" out4=fmax(out4,(FLOAT4)0);\n" +" out5=fmax(out5,(FLOAT4)0);\n" +" out6=fmax(out6,(FLOAT4)0);\n" +" out7=fmax(out7,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +" out1=clamp(out1,(FLOAT4)0,(FLOAT4)6);\n" +" out2=clamp(out2,(FLOAT4)0,(FLOAT4)6);\n" +" out3=clamp(out3,(FLOAT4)0,(FLOAT4)6);\n" +" out4=clamp(out4,(FLOAT4)0,(FLOAT4)6);\n" +" out5=clamp(out5,(FLOAT4)0,(FLOAT4)6);\n" +" out6=clamp(out6,(FLOAT4)0,(FLOAT4)6);\n" +" out7=clamp(out7,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" const int out_x_base=mul24(out_channel_block_idx,output_shape.y);\n" +" const int out_y_base=mul24(out_batch_block_idx,output_shape.x);\n" +" int out_x_idx=out_width_block_idx;\n" +" int out_y_idx=out_height_block_idx << 2;\n" +" const int remain_y=output_shape.x-out_y_idx;\n" +" int output_idx=out_x_base+out_x_idx;\n" +" int output_idy=out_y_base+out_y_idx;\n" +" \n" +" if(remain_y >= 4){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out1);\n" +" WI_F(output,(int2)(output_idx,output_idy+2),out2);\n" +" WI_F(output,(int2)(output_idx,output_idy+3),out3);\n" +" }else if(remain_y == 3){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out1);\n" +" WI_F(output,(int2)(output_idx,output_idy+2),out2);\n" +" }else if(remain_y == 2){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out1);\n" +" }else if(remain_y == 1){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" }\n" +" \n" +" if(out_channel_block_idx+1 >= out_channel_blocks) {\n" +" return;\n" +" }\n" +" output_idx += output_shape.y;\n" +" if(remain_y >= 4){\n" +" WI_F(output,(int2)(output_idx,output_idy),out4);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out5);\n" +" WI_F(output,(int2)(output_idx,output_idy+2),out6);\n" +" WI_F(output,(int2)(output_idx,output_idy+3),out7);\n" +" }else if(remain_y == 3){\n" +" WI_F(output,(int2)(output_idx,output_idy),out4);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out5);\n" +" WI_F(output,(int2)(output_idx,output_idy+2),out6);\n" +" }else if(remain_y == 2){\n" +" WI_F(output,(int2)(output_idx,output_idy),out4);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out5);\n" +" }else if(remain_y == 1){\n" +" WI_F(output,(int2)(output_idx,output_idy),out4);\n" +" }\n" +"}\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *kernel_ptr,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_BUFFER)\n" +" __global const FLOAT *weights,\n" +"#else\n" +" __read_only image2d_t weights,\n" +"#endif\n" +"#ifdef BIAS\n" +" __read_only image2d_t bias,\n" +"#endif\n" +" __write_only image2d_t output,\n" +" __private const int2 input_shape,\n" +" __private const int in_channel_block_length,\n" +" __private const int2 output_shape,\n" +" __private const int2 weights_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 padding_shape,\n" +" __private const int2 dilation_shape,\n" +" __private const int out_width_blocks,\n" +" __private const int out_channel_blocks,\n" +" __private const int out_height_blocks\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" ,__private const int blockDim\n" +" ,__private const int inChannel\n" +"#endif\n" +") {\n" +" const int output_channel_width_idx=get_global_id(0);\n" +" const int output_batch_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(output_channel_width_idx,output_batch_height_idx);\n" +" const int out_channel_block_idx=output_channel_width_idx/out_width_blocks;\n" +" const int out_width_block_idx=output_channel_width_idx % out_width_blocks;\n" +" const int out_height_block_idx=(output_batch_height_idx % out_height_blocks);\n" +" const int out_batch_block_idx=output_batch_height_idx/out_height_blocks;\n" +"#ifdef BIAS\n" +" FLOAT4 out0=RI_F(bias,SAMPLER,(int2)(out_channel_block_idx,0));\n" +"#else\n" +" FLOAT4 out0=(FLOAT4)0;\n" +"#endif\n" +" FLOAT4 out1=out0;\n" +" FLOAT4 out2=out0;\n" +" FLOAT4 out3=out0;\n" +" int in_width0=mad24(out_width_block_idx,stride_shape.y,-padding_shape.y);\n" +" int in_height0=mad24(out_height_block_idx,stride_shape.x<<2,-padding_shape.x);\n" +" int in_height1=in_height0+stride_shape.x;\n" +" int in_height2=in_height1+stride_shape.x;\n" +" int in_height3=in_height2+stride_shape.x;\n" +" int weight_size=mul24(weights_shape.y,weights_shape.x);\n" +" \n" +" const int weights_h_idx=mul24(out_channel_block_idx,weight_size);\n" +" const int batch_idx=mul24(out_batch_block_idx,input_shape.x);\n" +" \n" +" FLOAT4 in0,in1,in2,in3;\n" +" FLOAT4 weights0,weights1,weights2,weights3;\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4) || (defined USE_BUFFER)\n" +" const int weight_oc_offset=out_channel_blocks*weights_shape.x*weights_shape.y*4;\n" +"#endif\n" +" for (int in_channel_block_idx=0; in_channel_block_idx= input_shape.x));\n" +" int h1=select(in_height1+iy+batch_idx,-1,(in_height1+iy<0 || in_height1+iy >= input_shape.x));\n" +" int h2=select(in_height2+iy+batch_idx,-1,(in_height2+iy<0 || in_height2+iy >= input_shape.x));\n" +" int h3=select(in_height3+iy+batch_idx,-1,(in_height3+iy<0 || in_height3+iy >= input_shape.x));\n" +" for (int ix=0; ix= input_shape.y));\n" +" \n" +" in0=RI_F(input,SAMPLER,(int2)(w0,h0));\n" +" in1=RI_F(input,SAMPLER,(int2)(w0,h1));\n" +" in2=RI_F(input,SAMPLER,(int2)(w0,h2));\n" +" in3=RI_F(input,SAMPLER,(int2)(w0,h3));\n" +" \n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,kernel_ptr+weight_offset);\n" +" char4 charWeight1=vload4(0,kernel_ptr+weight_offset+weight_oc_offset);\n" +" char4 charWeight2=vload4(0,kernel_ptr+weight_offset+weight_oc_offset*2);\n" +" char4 charWeight3=vload4(0,kernel_ptr+weight_offset+weight_oc_offset*3);\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" weight_offset += 4;\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" uchar2 charWeightInt40=vload2(0,kernel_ptr+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,kernel_ptr+weight_offset/2+weight_oc_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weights0=mad(CONVERT_FLOAT4(charWeight0),scale0,offset0);\n" +" weights1=mad(CONVERT_FLOAT4(charWeight1),scale0,offset0);\n" +" weights2=mad(CONVERT_FLOAT4(charWeight2),scale0,offset0);\n" +" weights3=mad(CONVERT_FLOAT4(charWeight3),scale0,offset0);\n" +" weight_offset += 4;\n" +"#elif (defined USE_BUFFER)\n" +" weights0=vload4(0,weights+weight_offset);\n" +" weights1=vload4(0,weights+weight_offset+weight_oc_offset);\n" +" weights2=vload4(0,weights+weight_offset+weight_oc_offset*2);\n" +" weights3=vload4(0,weights+weight_offset+weight_oc_offset*3);\n" +" weight_offset += 4;\n" +"#else\n" +" weights0=RI_F(weights,SAMPLER,(int2)(weights_x_idx+0,weights_y_idx));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(weights_x_idx+1,weights_y_idx));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(weights_x_idx+2,weights_y_idx));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(weights_x_idx+3,weights_y_idx++));\n" +"#endif\n" +" PADZEROSVEC(in_channel_block_idx,inChannel,weights0,weights1,weights2,weights3);\n" +" CALCULATE_OUTPUT(0);\n" +" CALCULATE_OUTPUT(1);\n" +" CALCULATE_OUTPUT(2);\n" +" CALCULATE_OUTPUT(3);\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +" out1=fmax(out1,(FLOAT4)0);\n" +" out2=fmax(out2,(FLOAT4)0);\n" +" out3=fmax(out3,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +" out1=clamp(out1,(FLOAT4)0,(FLOAT4)6);\n" +" out2=clamp(out2,(FLOAT4)0,(FLOAT4)6);\n" +" out3=clamp(out3,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" const int out_x_base=mul24(out_channel_block_idx,output_shape.y);\n" +" const int out_y_base=mul24(out_batch_block_idx,output_shape.x);\n" +" int out_x_idx=out_width_block_idx;\n" +" int out_y_idx=out_height_block_idx << 2;\n" +" const int remain_y=output_shape.x-out_y_idx;\n" +" int output_idx=out_x_base+out_x_idx;\n" +" int output_idy=out_y_base+out_y_idx;\n" +" if(remain_y >= 4){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out1);\n" +" WI_F(output,(int2)(output_idx,output_idy+2),out2);\n" +" WI_F(output,(int2)(output_idx,output_idy+3),out3);\n" +" }else if(remain_y == 3){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out1);\n" +" WI_F(output,(int2)(output_idx,output_idy+2),out2);\n" +" }else if(remain_y == 2){\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" WI_F(output,(int2)(output_idx,output_idy+1),out1);\n" +" }else{\n" +" WI_F(output,(int2)(output_idx,output_idy),out0);\n" +" }\n" +"}\n" +; +const char* deconv_2d = +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void deconv_2d(GLOBAL_SIZE_3_DIMS\n" +" #ifdef USE_BUFFER\n" +" __global FLOAT* input,\n" +" __global FLOAT* weights,\n" +" #ifdef BIAS\n" +" __global FLOAT* bias,\n" +" #endif\n" +" __global FLOAT* output,\n" +" #else\n" +" __read_only image2d_t input,\n" +" __read_only image2d_t weights,\n" +" #ifdef BIAS\n" +" __read_only image2d_t bias,\n" +" #endif\n" +" __write_only image2d_t output,\n" +" #endif\n" +" __private const int2 input_shape,\n" +" __private const int2 output_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 align_shape,\n" +" __private const int2 padding_shape,\n" +" __private const int2 kernel_shape,\n" +" __private const int kernel_size,\n" +" __private const int in_channel_blocks,__private const int out_channel_blocks) {\n" +" const int out_channel_blocks_idx=get_global_id(0);\n" +" const int out_w_idx=get_global_id(1);\n" +" const int out_batch_height_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(out_channel_blocks_idx,out_w_idx,out_batch_height_idx);\n" +"#ifdef BIAS\n" +" #ifdef USE_BUFFER\n" +" FLOAT4 out0=vload4(out_channel_blocks_idx,bias);\n" +" #else\n" +" FLOAT4 out0=RI_F(bias,SAMPLER,(int2)(out_channel_blocks_idx,0));\n" +" #endif\n" +"#else\n" +" FLOAT4 out0=(FLOAT4)0;\n" +"#endif\n" +" const int out_b_idx=out_batch_height_idx/output_shape.x;\n" +" const int out_h_idx=out_batch_height_idx % output_shape.x;\n" +" \n" +" int kernel_start_x=max(0,(out_w_idx+align_shape.y)/stride_shape.y);\n" +" int kernel_start_y=max(0,(out_h_idx+align_shape.x)/stride_shape.x);\n" +" int deal_kernel_width=kernel_shape.y-mad24(kernel_start_x,stride_shape.y,padding_shape.y)+out_w_idx-1;\n" +" int deal_kernel_height=kernel_shape.x-mad24(kernel_start_y,stride_shape.x,padding_shape.x)+out_h_idx-1;\n" +" \n" +" \n" +" int kernel_x_0,kernel_x_1,kernel_x_2,kernel_x_3,kernel_y;\n" +" FLOAT4 in0;\n" +" FLOAT4 weights0,weights1,weights2,weights3;\n" +" for (int ic=0; ic= 0; k_y -= stride_shape.x,idx_h++) {\n" +" #ifdef USE_BUFFER\n" +" int in_width0=kernel_start_x;\n" +" for (int k_x=deal_kernel_width; k_x >= 0; k_x -= stride_shape.y) {\n" +" kernel_y=mad24(k_y,kernel_shape.y,k_x);\n" +" kernel_y=mad24(out_channel_blocks_idx,kernel_size,kernel_y);\n" +" //weights NC4HW4 [1,4*icC4,ocC4*kh*kw,1] xic4\n" +" //index: [0,kernel_x_0,kernel_y,0]\n" +" weights0=vload4(kernel_x_0*(out_channel_blocks*kernel_shape.x*kernel_shape.y)+kernel_y,weights);\n" +" weights1=vload4(kernel_x_1*(out_channel_blocks*kernel_shape.x*kernel_shape.y)+kernel_y,weights);\n" +" weights2=vload4(kernel_x_2*(out_channel_blocks*kernel_shape.x*kernel_shape.y)+kernel_y,weights);\n" +" weights3=vload4(kernel_x_3*(out_channel_blocks*kernel_shape.x*kernel_shape.y)+kernel_y,weights);\n" +" bool outBoundry=(idx_h<0 || idx_h >= input_shape.x || kernel_start_x<0 || in_width0 >= input_shape.y);\n" +" int inp_offset=(((out_b_idx*in_channel_blocks+ic)*input_shape.x+idx_h)*input_shape.y+in_width0)*4;\n" +" in0=outBoundry ? (FLOAT4)0 : vload4(0,input+inp_offset);\n" +" out0=mad(in0.x,weights0,out0);\n" +" out0=mad(in0.y,weights1,out0);\n" +" out0=mad(in0.z,weights2,out0);\n" +" out0=mad(in0.w,weights3,out0);\n" +" in_width0++;\n" +" }\n" +" #else\n" +" int in_idy=mad24(out_b_idx,input_shape.x,idx_h);\n" +" int in_hb_value=select(in_idy,-1,idx_h<0 || idx_h >= input_shape.x);\n" +" int in_width0=kernel_start_x;\n" +" for (int k_x=deal_kernel_width; k_x >= 0; k_x -= stride_shape.y) {\n" +" kernel_y=mad24(k_y,kernel_shape.y,k_x);\n" +" kernel_y=mad24(out_channel_blocks_idx,kernel_size,kernel_y);\n" +" weights0=RI_F(weights,SAMPLER,(int2)(kernel_x_0,kernel_y));\n" +" weights1=RI_F(weights,SAMPLER,(int2)(kernel_x_1,kernel_y));\n" +" weights2=RI_F(weights,SAMPLER,(int2)(kernel_x_2,kernel_y));\n" +" weights3=RI_F(weights,SAMPLER,(int2)(kernel_x_3,kernel_y));\n" +" int in_idx=mul24(ic,input_shape.y);\n" +" int in_width_value0 = in_width0; "" in_width_value0 = "" select(in_idx + in_width_value0, -1, (in_width_value0 < 0 || in_width_value0 >= input_shape.y)); "" in0=RI_F(input,SAMPLER,(int2)(in_width_value0,in_hb_value));\n" +" out0=mad(in0.x,weights0,out0);\n" +" out0=mad(in0.y,weights1,out0);\n" +" out0=mad(in0.z,weights2,out0);\n" +" out0=mad(in0.w,weights3,out0);\n" +" in_width0++;\n" +" }\n" +" #endif\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +"#ifdef USE_BUFFER\n" +" const int out_offset=(((out_b_idx*out_channel_blocks+out_channel_blocks_idx)*output_shape.x+out_h_idx)*output_shape.y+out_w_idx)*4;\n" +" vstore4(out0,0,output+out_offset);\n" +"#else\n" +" int out_image_width_idx=mad24(out_channel_blocks_idx,output_shape.y,out_w_idx);\n" +" WI_F(output,(int2)(out_image_width_idx,out_batch_height_idx),out0);\n" +"#endif\n" +"}\n" +"__kernel void iohw2oihw(__global const float* input_ptr,__global float* output_ptr,int plane_number,int input_channel,int output_channel) {\n" +" const int ic_index=get_global_id(0),oc_index=get_global_id(1);\n" +" if (ic_index >= input_channel || oc_index >= output_channel) {\n" +" return;\n" +" }\n" +" const int input_offset=(ic_index*output_channel+oc_index)*plane_number;\n" +" const int output_offset=(oc_index*input_channel+ic_index)*plane_number;\n" +" for (int i=0; i= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"inline float4 gelu(float4 in){\n" +" float4 value=0.79788458f*(0.044715f*in*in*in+in);\n" +" float4 x2=value*value;\n" +" float4 dst=value>(float4)5.0f ? (float4)1.0f : (value <= -(float4)5.0f ? -(float4)1.0f :\n" +" (value*(135135.0f+x2*(17325.0f+x2*(378.0f+x2))))/(135135.0f+x2*(62370.0f+x2*(3150.0f+x2*28.0f))));\n" +" return (1.0f+dst)*in*0.5f;\n" +"}\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void unary(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__write_only image2d_t output) {\n" +" const int channel_block_idx=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int hb=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(channel_block_idx,w,hb);\n" +" const int width=global_size_dim1;\n" +" const int pos=mad24(channel_block_idx,width,w);\n" +" float4 in=convert_float4(RI_DATA(input,SAMPLER,(int2)(pos,hb)));\n" +" OUTPUT_TYPE_I4 out=CONVERT_OUTPUT_I4(OPERATOR);\n" +" \n" +" WI_DATA(output,(int2)(pos,hb),out);\n" +"}\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* grid_sample_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"enum BorderMode {\n" +" BorderMode_ZEROS=0,\n" +" BorderMode_CLAMP=1,\n" +" BorderMode_REFLECTION=2,\n" +" BorderMode_MIN=BorderMode_ZEROS,\n" +" BorderMode_MAX=BorderMode_REFLECTION\n" +"};\n" +"float getPosition(float x,int range,int alignCorners){\n" +" float a=alignCorners == 1? 1.0f : 0.0f;\n" +" float b=alignCorners == 1? 0.0f : 1.0f;\n" +" return ((1.0f+x)*(range-a)-b)/2.0f;\n" +"}\n" +"static int CLAMP(int v,int min,int max) {\n" +" if ((v)max) {\n" +" (v)=max;\n" +" }\n" +" return v;\n" +"}\n" +"COMPUTE_FLOAT4 sample(int h,int w,\n" +" const int offset_base,\n" +" __global const FLOAT *buffer,\n" +" int height,int width,\n" +" enum BorderMode paddingMode){\n" +" if (h<0 || h >= height || w<0 || w >= width) {\n" +" if(paddingMode == BorderMode_ZEROS)\n" +" {\n" +" return 0.0f;\n" +" }\n" +" // Clearly,CLAMP is the right way to go for GridSamplePaddingMode_BORDER\n" +" // For GridSamplePaddingMode_REFLECTION,since we have reflected the values into (-1,1),\n" +" // the leftover reflections degrade to GridSamplePaddingMode_BORDER\n" +" h=CLAMP(h,0,height-1);\n" +" w=CLAMP(w,0,width-1);\n" +" }\n" +" int offset=(offset_base+h)*width+w;\n" +" return CONVERT_COMPUTE_FLOAT4(vload4(offset,buffer));\n" +"}\n" +"__kernel void nearest_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT* input,\n" +" __global const FLOAT* grid,\n" +" __global FLOAT* output,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int output_height,\n" +" __private const int output_width,\n" +" __private const int channelBlocks,\n" +" __private const enum BorderMode paddingMode,\n" +" __private const int alignCorners){\n" +" \n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_batch_idx=output_batch_height_block_idx/output_height;\n" +" const int output_height_idx=output_batch_height_block_idx % output_height;\n" +" // grid data format has been converted from nchw to nc4hw4\n" +" /* \n" +" (x1,x1,x1,x1) (y1,y2,y3,y4) \n" +" . . \n" +" . . slice\n" +" (x1,y1)...(xn,y1) . . \n" +" . . (xn,xn,xn,xn) (y1,y2,y3,y4)\n" +" . . <-> ---------------------------\n" +" . . (x1,x1,x1,x1) (y5,y6,y7,y8)\n" +" (x1,ym)...(xn,ym) . .\n" +" . . slice\n" +" . .\n" +" (xn,xn,xn,xn) (y5,y6,y7,y8)\n" +" ---------------------------\n" +" */\n" +" const int slice=output_height_idx/4;\n" +" const int slice_blocks=(output_height+3)/4;\n" +" // output_width_block_idx means gird y offset,2 means grid width\n" +" const int grid_offset=((output_batch_idx*slice_blocks+slice)*output_width+output_width_block_idx)*2;\n" +" COMPUTE_FLOAT4 grid_x=CONVERT_COMPUTE_FLOAT4(vload4(grid_offset,grid));\n" +" COMPUTE_FLOAT4 grid_y=CONVERT_COMPUTE_FLOAT4(vload4(grid_offset+1,grid));\n" +" const float arr[8]={grid_x.x,grid_y.x,grid_x.y,grid_y.y,grid_x.z,grid_y.z,grid_x.w,grid_y.w};\n" +" \n" +" // get grid x,y\n" +" const int arr_offset=output_height_idx % 4;\n" +" const float x=arr[2*arr_offset];\n" +" const float y=arr[2*arr_offset+1];\n" +" // convert grid x,y to input x,y coordinate range\n" +" float in_grid_x=getPosition(x,input_width,alignCorners);\n" +" float in_grid_y=getPosition(y,input_height,alignCorners);\n" +" // get nearest point\n" +" int nw=floor(in_grid_x+0.5f);\n" +" int nh=floor(in_grid_y+0.5f);\n" +" const int inp_offset_base=(output_batch_idx*channelBlocks+output_channel_block_idx)*input_height;\n" +" COMPUTE_FLOAT4 value=sample(nh,nw,inp_offset_base,input,input_height,input_width,paddingMode);\n" +" const int output_offset=((output_batch_idx*channelBlocks+output_channel_block_idx )*output_height+output_height_idx)*output_width+output_width_block_idx;\n" +" vstore4(CONVERT_FLOAT4(value),output_offset,output);\n" +"}\n" +"__kernel void bilinear_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT* input,\n" +" __global const FLOAT* grid,\n" +" __global FLOAT* output,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int output_height,\n" +" __private const int output_width,\n" +" __private const int channelBlocks,\n" +" __private const enum BorderMode paddingMode,\n" +" __private const int alignCorners){\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_batch_idx=output_batch_height_block_idx/output_height;\n" +" const int output_height_idx=output_batch_height_block_idx % output_height;\n" +" const int slice=output_height_idx/4;\n" +" const int slice_blocks=(output_height+3)/4;\n" +" // output_width_block_idx means gird y offset,2 means grid width\n" +" const int grid_offset=((output_batch_idx*slice_blocks+slice)*output_width+output_width_block_idx)*2;\n" +" COMPUTE_FLOAT4 grid_x=CONVERT_COMPUTE_FLOAT4(vload4(grid_offset,grid));\n" +" COMPUTE_FLOAT4 grid_y=CONVERT_COMPUTE_FLOAT4(vload4(grid_offset+1,grid));\n" +" const float arr[8]={grid_x.x,grid_y.x,grid_x.y,grid_y.y,grid_x.z,grid_y.z,grid_x.w,grid_y.w};\n" +" \n" +" // get grid x,y\n" +" const int arr_offset=output_height_idx % 4;\n" +" const float x=arr[2*arr_offset];\n" +" const float y=arr[2*arr_offset+1];\n" +" // convert grid x,y to input x,y coordinate range\n" +" float in_grid_x=getPosition(x,input_width,alignCorners);\n" +" float in_grid_y=getPosition(y,input_height,alignCorners);\n" +" int in_h0=floor(in_grid_y);\n" +" int in_w0=floor(in_grid_x);\n" +" int in_h1=ceil(in_grid_y);\n" +" int in_w1=ceil(in_grid_x);\n" +" float x_weight=in_w1-in_grid_x;\n" +" float y_weight=in_h1-in_grid_y;\n" +" // bilinear interpolation\n" +" const int inp_offset_base=(output_batch_idx*channelBlocks+output_channel_block_idx)*input_height;\n" +" COMPUTE_FLOAT4 i00=sample(in_h0,in_w0,inp_offset_base,input,input_height,input_width,paddingMode);\n" +" COMPUTE_FLOAT4 i01=sample(in_h0,in_w1,inp_offset_base,input,input_height,input_width,paddingMode);\n" +" COMPUTE_FLOAT4 i10=sample(in_h1,in_w0,inp_offset_base,input,input_height,input_width,paddingMode);\n" +" COMPUTE_FLOAT4 i11=sample(in_h1,in_w1,inp_offset_base,input,input_height,input_width,paddingMode);\n" +" COMPUTE_FLOAT4 value=CONVERT_COMPUTE_FLOAT4(((COMPUTE_FLOAT4)x_weight*CONVERT_COMPUTE_FLOAT4(i00)+(COMPUTE_FLOAT4)(1.0f-x_weight)*CONVERT_COMPUTE_FLOAT4(i01))*(COMPUTE_FLOAT4)y_weight +\n" +" ((COMPUTE_FLOAT4)x_weight*CONVERT_COMPUTE_FLOAT4(i10)+(COMPUTE_FLOAT4)(1.0f-x_weight)*CONVERT_COMPUTE_FLOAT4(i11))*(COMPUTE_FLOAT4)(1.0f- y_weight));\n" +" \n" +" const int output_offset=((output_batch_idx*channelBlocks+output_channel_block_idx )*output_height+output_height_idx)*output_width+output_width_block_idx;\n" +" vstore4(CONVERT_FLOAT4(value),output_offset,output);\n" +"}\n" +; +#endif +const char* interp = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void interp(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__write_only image2d_t output,\n" +" __private const float height_scale,__private const float width_scale,\n" +" __private const float height_offset,__private const float width_offset,\n" +" __private const int input_height,__private const int input_width,\n" +" __private const int out_height) {\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_channel_block_idxs=global_size_dim0;\n" +" const int output_width=global_size_dim1;\n" +" const int output_batch_idx=output_batch_height_block_idx/out_height;\n" +" const int output_height_idx=output_batch_height_block_idx % out_height;\n" +" const float scale_height=output_height_idx*height_scale+height_offset;\n" +" const float scale_width=output_width_block_idx*width_scale+width_offset;\n" +"#define CLAMP(val,min_val,max_val) max(min(val,max_val),min_val)\n" +" const int height_floor=(int)floor(scale_height);\n" +" const int height_lf=CLAMP(height_floor,0,input_height-1);\n" +" const int height_uf=CLAMP(height_floor+1,0,input_height-1);\n" +" \n" +" const int width_floor=(int)floor(scale_width);\n" +" const int width_lf=CLAMP(width_floor,0,input_width-1);\n" +" const int width_uf=CLAMP(width_floor+1,0,input_width-1);\n" +" const float height_gap=scale_height-height_floor;\n" +" const float width_gap=scale_width-width_floor;\n" +" const int input_width_offset=mul24(output_channel_block_idx,input_width);\n" +" const int input_height_offset=mul24(output_batch_idx,input_height);\n" +" float4 top_left =\n" +" read_imagef(input,SAMPLER,(int2)(input_width_offset+width_lf,input_height_offset+height_lf));\n" +" float4 top_right =\n" +" read_imagef(input,SAMPLER,(int2)(input_width_offset+width_uf,input_height_offset+height_lf));\n" +" float4 bottom_left =\n" +" read_imagef(input,SAMPLER,(int2)(input_width_offset+width_lf,input_height_offset+height_uf));\n" +" float4 bottom_right =\n" +" read_imagef(input,SAMPLER,(int2)(input_width_offset+width_uf,input_height_offset+height_uf));\n" +" float4 top=mad((top_right-top_left),width_gap,top_left);\n" +" float4 bottom=mad((bottom_right-bottom_left),width_gap,bottom_left);\n" +" float4 out=mad((bottom-top),height_gap,top);\n" +" const int out_image_w=mad24(output_channel_block_idx,output_width,output_width_block_idx);\n" +" const int out_image_h=mad24(output_batch_idx,out_height,output_height_idx);\n" +" write_imagef(output,(int2)(out_image_w,out_image_h),out);\n" +"}\n" +; +const char* select = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void select_img(GLOBAL_SIZE_2_DIMS\n" +" __read_only image2d_t input,\n" +" __read_only image2d_t input0,\n" +" __read_only image2d_t input1,\n" +" __write_only image2d_t output\n" +" ) {\n" +" const int idx=get_global_id(0);\n" +" const int idy=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(idx,idy);\n" +" int4 select_vec=read_imagei(input,SAMPLER,(int2)(idx,idy));\n" +"#ifdef INSIZE1_EUQAL_1\n" +" FLOAT4 in0=RI_F(input0,SAMPLER,(int2)(0,0));\n" +" in0=(FLOAT4)(in0.x);\n" +"#else\n" +" FLOAT4 in0=RI_F(input0,SAMPLER,(int2)(idx,idy));\n" +"#endif\n" +" \n" +"#ifdef INSIZE2_EUQAL_1\n" +" FLOAT4 in1=RI_F(input1,SAMPLER,(int2)(0,0));\n" +" in1=(FLOAT4)(in1.x);\n" +"#else\n" +" FLOAT4 in1=RI_F(input1,SAMPLER,(int2)(idx,idy));\n" +"#endif\n" +" FLOAT4 out=select(in1,in0,select_vec == (int4)1);\n" +" WI_F(output,(int2)(idx,idy),out);\n" +"}\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* range_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void range_buf(GLOBAL_SIZE_3_DIMS\n" +" __global const INPUT_TYPE* input0,\n" +" __global const INPUT_TYPE* input2,\n" +" __global OUTPUT_TYPE* output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel,\n" +" __private const int channelBlock\n" +" ) {\n" +" const int width_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/channelBlock;\n" +" const int channel_idx=batch_channel_idx % channelBlock;\n" +" \n" +" const int offset=((((batch_idx*channelBlock)+channel_idx)*height+height_idx)*width+width_idx)*4;\n" +" const int channel4=channel_idx << 2;\n" +" int index=(((batch_idx*channel)+channel4)*height+height_idx)*width+width_idx;\n" +" int size=height*width;\n" +" int4 index4=(int4)(index,index+size,index+size*2,index+size*3);\n" +" INPUT_TYPE start=input0[0];\n" +" INPUT_TYPE step=input2[0];\n" +" OUTPUT_TYPE4 value=(OUTPUT_TYPE4)start+CONVERT_OUTPUT4(index4)*(OUTPUT_TYPE4)step;\n" +" vstore4(value,0,output+offset);\n" +"}\n" +; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* self_attention_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"#define DEAL_HEAD_DIM_NOT_ALIGN "" if(hd * 4 + 3 >= head_dim) {"" temp_0.w = (FLOAT)0;"" temp_1.w = (FLOAT)0;"" temp_2.w = (FLOAT)0;"" temp_3.w = (FLOAT)0;"" }"" if(hd * 4 + 2 >= head_dim) {"" temp_0.z = (FLOAT)0;"" temp_1.z = (FLOAT)0;"" temp_2.z = (FLOAT)0;"" temp_3.z = (FLOAT)0;"" }"" if(hd * 4 + 1 >= head_dim) {"" temp_0.y = (FLOAT)0;"" temp_1.y = (FLOAT)0;"" temp_2.y = (FLOAT)0;"" temp_3.y = (FLOAT)0;"" }\n" +"#define DEAL_SEQ_LEN_NOT_ALIGN "" if(4 * sl + 3 >= seq_len) {"" temp_3 = (FLOAT4)0;"" }"" if(4 * sl + 2 >= seq_len) {"" temp_2 = (FLOAT4)0;"" }"" if(4 * sl + 1 >= seq_len) {"" temp_1 = (FLOAT4)0;"" }\n" +"__kernel void split_transpose_qkv(GLOBAL_SIZE_3_DIMS\n" +" __global const FLOAT *input,// [Batch,seqLen/4,mNumHead*3*mHeadDim,4]\n" +" __global FLOAT *output_q,// [Batch*mNumHead,head_dim_pack_k,seq_len_pack_mn/qSeqSplitNum]\n" +" __global FLOAT *output_k,// [Batch*mNumHead,head_dim_pack_k,seq_len_pack_mn]\n" +" __global FLOAT *output_v,// [Batch*mNumHead,ROUND_UP(seqLen,tile),head_dim_pack_mn]\n" +" __private const int seq_len_pack_mn,\n" +" __private const int seq_len_piece,\n" +" __private const int head_dim_pack_mn,\n" +" __private const int head_dim_pack_k,\n" +" __private const int seq_len,\n" +" __private const int head_num,\n" +" __private const int head_dim,\n" +" __private const int seq_index\n" +") {\n" +" const int sl=get_global_id(0); // seqLen_4\n" +" const int hd=get_global_id(1); // mHeadDim_4\n" +" const int z=get_global_id(2); // Batch*mNumHead\n" +" DEAL_NON_UNIFORM_DIM3(sl,hd,z);\n" +" \n" +" const int b=z/head_num;\n" +" const int hn=z % head_num;\n" +" \n" +" const int seq_len_4=(seq_len+3)/4;\n" +" const int offset_q=((b*head_num+hn)*head_dim_pack_k+4*hd)*seq_len_piece+4*sl;\n" +" if(seq_index>0) {\n" +" // fill output_q only\n" +" if(sl*4 >= seq_len || hd*4 >= head_dim) {\n" +" if(hd*4= seq_len || hd*4 >= head_dim) {\n" +" if(hd*4 reduce: inside\n" +"__kernel void softmax_inside(GLOBAL_SIZE_3_DIMS\n" +" __global const FLOAT *input,// [batch*mNumHead,ROUND_UP(seqLen,tile),ROUND_UP(seqLen,tile)]\n" +" __global FLOAT *output,\n" +" __private const int inside_len,\n" +" __private const int4 shape // [batch*mNumHead,ROUND_UP(seqLen,tile),ROUND_UP(seqLen,tile)]\n" +" ) {\n" +" const int inside=get_global_id(0);\n" +" const int axis=get_global_id(1);\n" +" const int outside=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(inside,axis,outside);\n" +" const int offset=(outside*shape.y+axis)*shape.z+0;\n" +" int lid=get_local_id(0);\n" +" float local sum[SOFTMAX_LOCAL_SIZE];\n" +" /*Compute Max */\n" +" float maxValue=(float)(-FLT_MAX);\n" +" // clip to seq_len\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid [N Y X]\n" +"__kernel void trans_3d_buf(__global const FLOAT* input,\n" +" __global FLOAT* output,\n" +" __private const int batch,\n" +" __private const int width,\n" +" __private const int height\n" +") {\n" +" int b=get_global_id(2);\n" +" \n" +" const int lidw=get_local_id(0);\n" +" const int lidh=get_local_id(1);\n" +" // group id\n" +" const int w=get_group_id(0)*WGSW;\n" +" const int h=get_group_id(1)*WGSH;\n" +" int iw=lidw;\n" +" int jh=lidh;\n" +" \n" +" __local FLOAT4 localData[WGSW][WGSH/4];//w64h64\n" +" \n" +" #pragma unroll\n" +" for(int i=0; i= seq_len_4) {\n" +" return;\n" +" }\n" +" const int seq_len_pack=seq_len_piece;//((seq_len+tile-1)/tile)*tile;\n" +" const int head_dim_pack=((head_dim+tile-1)/tile)*tile;\n" +" \n" +" const int offset_inp=((b*head_num+hn)*head_dim_pack+4*hd)*seq_len_pack+4*sl;\n" +" \n" +" const int offset_out=(((b*seq_len_4+seq_index*seq_len_piece/4+sl)*head_num+hn)*head_dim+4*hd)*4;\n" +" \n" +" // Q\n" +" FLOAT4 temp_0=vload4(0,input+offset_inp);\n" +" FLOAT4 temp_1=vload4(0,input+offset_inp+seq_len_pack);\n" +" FLOAT4 temp_2=vload4(0,input+offset_inp+2*seq_len_pack);\n" +" FLOAT4 temp_3=vload4(0,input+offset_inp+3*seq_len_pack);\n" +" \n" +" vstore4(temp_0,0,output+offset_out);\n" +" if(4*hd+1>head_dim) return;\n" +" vstore4(temp_1,0,output+offset_out+4);\n" +" if(4*hd+2>head_dim) return;\n" +" vstore4(temp_2,0,output+offset_out+8);\n" +" if(4*hd+3>head_dim) return;\n" +" vstore4(temp_3,0,output+offset_out+12);\n" +"}\n" +; +#endif +const char* performance = +"#define MAD_V4(x, y) "" x = mad(y, x, y); "" y = mad(x, y, x); "" x = mad(y, x, y); "" y=mad(x,y,x);\n" +"#define MAD_V16(x, y) "" MAD_V4(x, y); "" MAD_V4(x, y); "" MAD_V4(x, y); "" MAD_V4(x,y);\n" +"#define MAD_V64(x, y) "" MAD_V16(x, y); "" MAD_V16(x, y); "" MAD_V16(x, y); "" MAD_V16(x,y);\n" +"#define MAD_V128(x, y) "" MAD_V64(x, y); "" MAD_V64(x, y); "" MAD_V64(x, y); "" MAD_V64(x,y);\n" +"#define MAD_V256(x, y) "" MAD_V128(x, y); "" MAD_V128(x, y); "" MAD_V128(x, y); "" MAD_V128(x,y);\n" +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__kernel void float_precision(__global float* output_ptr,float mul_value) {\n" +" float mul_x=mul_value;\n" +" float mul_y=(float)get_local_id(0);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" output_ptr[get_global_id(0)]=mul_y;\n" +"}\n" +"__kernel void half4_precision(__global half* output_ptr,float mul_value) {\n" +" half mul=(half)mul_value;\n" +" half4 mul_x=(half4)(mul);\n" +" half4 mul_y=(half4)get_local_id(0);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" MAD_V256(mul_x,mul_y);\n" +" output_ptr[get_global_id(0)]=(mul_y.S0)+(mul_y.S1)+(mul_y.S2)+(mul_y.S3);\n" +"}\n" +; +const char* winogradTransformSource2_3_1 = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void winogradTransformSource(__read_only image2d_t uInput,// 0\n" +" __write_only image2d_t uOutput,__private const int unitWidth,\n" +" __private const int unitHeight,// 3\n" +" __private const int padX,__private const int padY,\n" +" __private const int srcWidth,// 6\n" +" __private const int srcHeight,__private const int srcChannelC4,\n" +" __private const int batchOffset) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" if (pos.x= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S00=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S10=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S20=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S30=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S01=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S11=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S21=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S31=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S02=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S12=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S22=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S32=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S03=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S13=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S23=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S33=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" FLOAT4 m00=+S00-S02;\n" +" FLOAT4 m10=+S10-S12;\n" +" FLOAT4 m20=+S20-S22;\n" +" FLOAT4 m30=+S30-S32;\n" +" FLOAT4 m01=+(FLOAT)0.5f*S01+(FLOAT)0.5f*S02;\n" +" FLOAT4 m11=+(FLOAT)0.5f*S11+(FLOAT)0.5f*S12;\n" +" FLOAT4 m21=+(FLOAT)0.5f*S21+(FLOAT)0.5f*S22;\n" +" FLOAT4 m31=+(FLOAT)0.5f*S31+(FLOAT)0.5f*S32;\n" +" FLOAT4 m02=-(FLOAT)0.5f*S01+(FLOAT)0.5f*S02;\n" +" FLOAT4 m12=-(FLOAT)0.5f*S11+(FLOAT)0.5f*S12;\n" +" FLOAT4 m22=-(FLOAT)0.5f*S21+(FLOAT)0.5f*S22;\n" +" FLOAT4 m32=-(FLOAT)0.5f*S31+(FLOAT)0.5f*S32;\n" +" FLOAT4 m03=-S01+S03;\n" +" FLOAT4 m13=-S11+S13;\n" +" FLOAT4 m23=-S21+S23;\n" +" FLOAT4 m33=-S31+S33;\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*0),+m00-m20);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*1),+(FLOAT)0.5f*m10+(FLOAT)0.5f*m20);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*2),-(FLOAT)0.5f*m10+(FLOAT)0.5f*m20);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*3),-m10+m30);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*4),+m01-m21);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*5),+(FLOAT)0.5f*m11+(FLOAT)0.5f*m21);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*6),-(FLOAT)0.5f*m11+(FLOAT)0.5f*m21);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*7),-m11+m31);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*8),+m02-m22);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*9),+(FLOAT)0.5f*m12+(FLOAT)0.5f*m22);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*10),-(FLOAT)0.5f*m12+(FLOAT)0.5f*m22);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*11),-m12+m32);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*12),+m03-m23);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*13),+(FLOAT)0.5f*m13+(FLOAT)0.5f*m23);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*14),-(FLOAT)0.5f*m13+(FLOAT)0.5f*m23);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*15),-m13+m33);\n" +" }\n" +" }\n" +"}\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* gemv_conv1x1_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_DIM2 "" __private int global_size_dim0,__private int global_size_dim1,\n" +"#define UNIFORM_BOUNDRY_CHECK(index0, index1) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +"#define UCHAR16_TO_2CHAR16(a, b, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; "" b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; "" b.s8=(c.sc >> 4)-8; b.s9=(c.sc & 15)-8; b.sa=(c.sd >> 4)-8; b.sb=(c.sd & 15)-8; b.sc=(c.se >> 4)-8; b.sd=(c.se & 15)-8; b.se=(c.sf >> 4)-8; b.sf=(c.sf & 15)-8;\n" +"#define UCHAR8_TO_CHAR16(a, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8=(c.s4 >> 4)-8; a.s9=(c.s4 & 15)-8; a.sa=(c.s5 >> 4)-8; a.sb=(c.s5 & 15)-8; a.sc=(c.s6 >> 4)-8; a.sd=(c.s6 & 15)-8; a.se=(c.s7 >> 4)-8; a.sf=(c.s7 & 15)-8;\n" +"#define DOT16X16(a, b, c) "" c += dot(a.s0123, b.s0123); "" c += dot(a.s4567, b.s4567); "" c += dot(a.s89ab, b.s89ab); "" c += dot(a.scdef,b.scdef);\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" #define PADZEROS(k, channel, data) {"" COMPUTE_FLOAT* ptr = (COMPUTE_FLOAT*)&data; "" int remain = k + 15 - channel; "" for(int r = remain; r >= 0; r--){ "" ptr[15 - remain] = 0; "" } "" }\n" +"#else\n" +" #define PADZEROS(k,channel,data)\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void gemm_conv_c4_buf(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT* output,\n" +" __private const int dstChannelC4,\n" +" __private const int srcChannelC4,\n" +" __private const int srcChannel,\n" +" __private const int batch,\n" +" __private const int height,\n" +" __private const int width,\n" +" __private const int blockNum,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" UNIFORM_BOUNDRY_CHECK(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/width;\n" +" const int out_w_idx=out_c_w_idx % width;\n" +"#ifdef BACTH_BLOCK4\n" +" const int out_b_idx=(out_b_h_idx/height) << 2;\n" +"#else\n" +" const int out_b_idx=out_b_h_idx/height;\n" +"#endif\n" +" const int out_h_idx=out_b_h_idx % height;\n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out=bias0;\n" +"#ifdef BACTH_BLOCK4\n" +" COMPUTE_FLOAT4 out1=bias0,out2=bias0,out3=bias0;\n" +" int input_offset1=(((out_b_idx+1)*srcChannelC4*height+out_h_idx)*width+out_w_idx)*4;\n" +" int input_offset2=(((out_b_idx+2)*srcChannelC4*height+out_h_idx)*width+out_w_idx)*4;\n" +" int input_offset3=(((out_b_idx+3)*srcChannelC4*height+out_h_idx)*width+out_w_idx)*4;\n" +" bool isValidBatch1=out_b_idx+1= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void buffer_set_zero(\n" +" GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(x,y);\n" +" \n" +" output[y*global_size_dim0+x]=(OUTPUT_TYPE)(0);\n" +"}\n" +"__kernel void image_set_zero(\n" +" GLOBAL_SIZE_2_DIMS\n" +" __write_only image2d_t output\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(x,y);\n" +" WI_DATA(output,(int2)(x,y),(OUTPUT_TYPE_I4)(0));\n" +"}\n" +"__kernel void raster_buffer_direct(\n" +" GLOBAL_SIZE_3_DIMS\n" +" __read_only image2d_t input,\n" +" __private const int inputOffset,\n" +" __private const int combineSrcOffset,\n" +" __private const int inputStride0,\n" +" __private const int inputStride1,\n" +" __private const int inputStride2,\n" +" __private const int src_width,\n" +" __private const int src_height,\n" +" __private const int src_channel,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int outputOffset,\n" +" __private const int combineDstOffset,\n" +" __private const int outputStride0,\n" +" __private const int outputStride1,\n" +" __private const int outputStride2,\n" +" __private const int global_size0\n" +" ) {\n" +" const int idx=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" const int z=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(idx,y,z);\n" +" const int x=idx % global_size0;\n" +" const int id=idx/global_size0;\n" +" \n" +" int inputIndex=inputOffset+id*combineSrcOffset+z*inputStride0+y*inputStride1+x*inputStride2;\n" +" int outputIndex=outputOffset+id*combineDstOffset+z*outputStride0+y*outputStride1+x*outputStride2;\n" +"#ifdef INPUT_DATA_FORMAT_NHWC\n" +" int in_c=inputIndex % src_channel; inputIndex /= src_channel;\n" +" int in_w=inputIndex % src_width; inputIndex /= src_width;\n" +" int in_h=inputIndex % src_height;\n" +" int in_b=inputIndex/src_height;\n" +"#else\n" +" int in_w=inputIndex % src_width; inputIndex /= src_width;\n" +" int in_h=inputIndex % src_height; inputIndex /= src_height;\n" +" int in_c=inputIndex % src_channel;\n" +" int in_b=inputIndex/src_channel;\n" +"#endif\n" +" int2 coord=(int2)((in_c/4)*src_width+in_w,in_b*src_height+in_h);\n" +" INPUT_TYPE_I4 value=RI_DATA(input,SAMPLER,coord);\n" +" INPUT_TYPE_I* value_ptr=(INPUT_TYPE_I*)&value;\n" +" output[outputIndex]=(OUTPUT_TYPE)value_ptr[in_c % 4];\n" +"}\n" +"__kernel void raster_image(\n" +" GLOBAL_SIZE_3_DIMS\n" +" __read_only image2d_t input,\n" +" __private const int inputOffset,\n" +" __private const int inputStride0,\n" +" __private const int inputStride1,\n" +" __private const int inputStride2,\n" +" __private const int inputHeight,\n" +" __private const int inputWidth,\n" +" __private const int inputChannel,\n" +" __write_only image2d_t output,\n" +" __private const int outputOffset,\n" +" __private const int outputStride0,\n" +" __private const int outputStride1,\n" +" __private const int outputStride2,\n" +" __private const int outputHeight,\n" +" __private const int outputWidth,\n" +" __private const int outputChannel\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" const int z=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(x,y,z);\n" +" \n" +" int inputIndex=inputOffset+(z*inputStride0+y*inputStride1+x*inputStride2)*4;\n" +" int outputIndex=outputOffset+(z*outputStride0+y*outputStride1+x*outputStride2)*4;\n" +" int inp_idx_n=inputIndex/((inputChannel+3)/4*inputHeight*inputWidth*4);\n" +" int inputIndex_left=inputIndex % ((inputChannel+3)/4*inputHeight*inputWidth*4);\n" +" int inp_idx_c4=inputIndex_left/(inputHeight*inputWidth*4);\n" +" inputIndex_left=inputIndex_left % (inputHeight*inputWidth*4);\n" +" int inp_idx_h=inputIndex_left/(inputWidth*4);\n" +" inputIndex_left=inputIndex_left % (inputWidth*4);\n" +" int inp_idx_w=inputIndex_left/4;\n" +" \n" +" int out_idx_n=outputIndex/((outputChannel+3)/4*outputHeight*outputWidth*4);\n" +" int outputIndex_left=outputIndex % ((outputChannel+3)/4*outputHeight*outputWidth*4);\n" +" int out_idx_c4=outputIndex_left/(outputHeight*outputWidth*4);\n" +" outputIndex_left=outputIndex_left % (outputHeight*outputWidth*4);\n" +" int out_idx_h=outputIndex_left/(outputWidth*4);\n" +" outputIndex_left=outputIndex_left % (outputWidth*4);\n" +" int out_idx_w=outputIndex_left/4;\n" +" \n" +" int inp_idx0=inp_idx_c4*inputWidth+inp_idx_w;\n" +" int inp_idx1=inp_idx_n*inputHeight+inp_idx_h;\n" +" int out_idx0=out_idx_c4*outputWidth+out_idx_w;\n" +" int out_idx1=out_idx_n*outputHeight+out_idx_h;\n" +" INPUT_TYPE_I4 out=RI_DATA(input,SAMPLER,(int2)(inp_idx0,inp_idx1));\n" +" WI_DATA(output,(int2)(out_idx0,out_idx1),CONVERT_OUTPUT_I4(out));\n" +"}\n" +; #ifndef MNN_OPENCL_BUFFER_CLOSED #ifdef MNN_SUPPORT_INTEL_SUBGROUP -{ - "conv_2d_c1_subgroup_buf", - { 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} - }, +const char* conv_2d_c1_subgroup_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#pragma OPENCL EXTENSION cl_intel_subgroups : enable\n" +"#ifdef MNN_SUPPORT_FP16\n" +"#define GROUP_READ(ptr,offset) as_half(intel_sub_group_block_read_us((const __global ushort*)(ptr)+(offset)))\n" +"#define GROUP_READ2(ptr,offset) as_half2(intel_sub_group_block_read_us2((const __global ushort*)(ptr)+(offset)))\n" +"#define GROUP_READ4(ptr,offset) as_half4(intel_sub_group_block_read_us4((const __global ushort*)(ptr)+(offset)))\n" +"#define GROUP_READ8(ptr,offset) as_half8(intel_sub_group_block_read_us8((const __global ushort*)(ptr)+(offset)))\n" +"#define GROUP_WRITE(ptr,offset,val) intel_sub_group_block_write_us((const __global ushort*)(ptr)+(offset),as_ushort(val))\n" +"#define GROUP_WRITE2(ptr,offset,val) intel_sub_group_block_write_us2((const __global ushort*)(ptr)+(offset),as_ushort2(val))\n" +"#define GROUP_WRITE4(ptr,offset,val) intel_sub_group_block_write_us4((const __global ushort*)(ptr)+(offset),as_ushort4(val))\n" +"#define GROUP_WRITE8(ptr,offset,val) intel_sub_group_block_write_us8((const __global ushort*)(ptr)+(offset),as_ushort8(val))\n" +"#define GROUP_SHUFFLE(data,id) as_half(intel_sub_group_shuffle(as_ushort(data),id))\n" +"#define GROUP_SHUFFLE2(data,id) as_half2(intel_sub_group_shuffle(as_ushort2(data),id))\n" +"#define GROUP_SHUFFLE4(data,id) as_half4(intel_sub_group_shuffle(as_ushort4(data),id))\n" +"#define GROUP_SHUFFLE8(data,id) as_half8(intel_sub_group_shuffle(as_ushort8(data),id))\n" +"#else\n" +"#define GROUP_READ(ptr,offset) as_float(intel_sub_group_block_read((const __global uint*)(ptr)+(offset)))\n" +"#define GROUP_READ2(ptr,offset) as_float2(intel_sub_group_block_read2((const __global uint*)(ptr)+(offset)))\n" +"#define GROUP_READ4(ptr,offset) as_float4(intel_sub_group_block_read4((const __global uint*)(ptr)+(offset)))\n" +"#define GROUP_READ8(ptr,offset) as_float8(intel_sub_group_block_read8((const __global uint*)(ptr)+(offset)))\n" +"#define GROUP_WRITE(ptr,offset,val) intel_sub_group_block_write((const __global uint*)(ptr)+(offset),as_uint(val))\n" +"#define GROUP_WRITE2(ptr,offset,val) intel_sub_group_block_write2((const __global uint*)(ptr)+(offset),as_uint2(val))\n" +"#define GROUP_WRITE4(ptr,offset,val) intel_sub_group_block_write4((const __global uint*)(ptr)+(offset),as_uint4(val))\n" +"#define GROUP_WRITE8(ptr,offset,val) intel_sub_group_block_write8((const __global uint*)(ptr)+(offset),as_uint8(val))\n" +"#define GROUP_SHUFFLE(data,id) intel_sub_group_shuffle(data,id)\n" +"#define GROUP_SHUFFLE2(data,id) intel_sub_group_shuffle(data,id)\n" +"#define GROUP_SHUFFLE4(data,id) intel_sub_group_shuffle(data,id)\n" +"#define GROUP_SHUFFLE8(data,id) intel_sub_group_shuffle(data,id)\n" +"#endif\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_2d_buf_subgroup_c1_c4_b2(\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __global FLOAT* weights,\n" +" __global FLOAT* biases,\n" +" __private const int pad_width,\n" +" __private const int pad_height,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int output_width,\n" +" __private const int output_height,\n" +" __private const int output_channel,\n" +" __private const int x_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right\n" +")\n" +"{\n" +" const int f_block=get_group_id(1);\n" +" const int lid=get_sub_group_local_id();\n" +" const int b=get_global_id(2);\n" +" const int xy=get_global_id(0);\n" +" const int x=(xy % x_blocks) << 1;\n" +" const int y=(xy/x_blocks);\n" +" const int input_x=x*STRIDE_WIDTH-pad_width;\n" +" const int input_y=y*STRIDE_HEIGHT-pad_height;\n" +" const uint input_x_pitch=1;\n" +" const uint input_y_pitch=input_x_pitch*input_width;\n" +" const uint input_f_pitch=input_y_pitch*input_height;\n" +" const uint input_b_pitch=input_f_pitch*INPUT_CHANNEL;\n" +" const uint input_offset=b*input_b_pitch +\n" +" input_y*input_y_pitch +\n" +" input_x*input_x_pitch;\n" +" const uint output_pack=(output_channel+3)/4;\n" +" const uint output_x_pitch=4;\n" +" const uint output_y_pitch=output_x_pitch*output_width;\n" +" const uint output_fs_pitch=output_y_pitch*output_height;\n" +" const uint output_b_pitch=output_fs_pitch*output_pack;\n" +" \n" +" \n" +" const uint output_offset=b*output_b_pitch +\n" +" f_block*4*output_fs_pitch +\n" +" y*output_y_pitch +\n" +" x*output_x_pitch;\n" +" const uint filter_isv_pitch=16;\n" +" const uint filter_x_pitch=256;\n" +" const uint filter_y_pitch=filter_x_pitch*FILTER_WIDTH;\n" +" const uint filter_is_pitch=filter_y_pitch*FILTER_HEIGHT;\n" +" const uint filter_os_pitch=filter_is_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint filter_offset=f_block*filter_os_pitch;\n" +" uint bias_offset=f_block*16;\n" +" COMPUTE_FLOAT2 dst=(COMPUTE_FLOAT2)(GROUP_READ(biases,bias_offset));\n" +" \n" +" FLOAT line_cache[INPUT_CHANNEL*INPUT_BLOCK_SIZE];\n" +" for (int ic=0; ic= 0 && input_y+yb= 0 && input_x+xb= output_channel) {\n" +" for (int i=0; i<2 && (x+i)= 0 && input_y+yb= 0 && input_x+xb= output_channel) {\n" +" for (int i=0; i<4 && (x+i)= 0 && input_y+yb= 0 && input_x+xb= output_channel) {\n" +" for (int i=0; i<8 && (x+i)= 0 && input_y+yb= 0 && input_x+xb= output_channel) {\n" +" for (int i=0; i<2; i++) {\n" +" if ((f_block*16+lid= 0 && input_y+yb= 0 && input_x+xb= output_channel) {\n" +" for (int i=0; i<4; i++) {\n" +" if ((f_block*16+lid= 0 && input_y+yb= 0 && input_x+xb= output_channel) {\n" +" for (int i=0; i<8; i++) {\n" +" if ((f_block*16+lid= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"#define MOD_NUM 15\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" #define PADZEROSVEC(k, channel, data0, data1, data2, data3) "" data0 = (k << 2) < channel ? data0 : 0; "" data1 = (k << 2) + 1 < channel ? data1 : 0; "" data2 = (k << 2) + 2 < channel ? data2 : 0; "" data3=(k << 2)+3> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" \n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" }\n" +" weight_offset += 4*filter_hw.y;\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" \n" +"}\n" +"__kernel\n" +"void conv_2d_int_c4h1w2(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#else\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,//generate width's num\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=(out_c_w_idx % out_w_blocks) << 1;\n" +" const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" \n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out0=bias0;\n" +" COMPUTE_FLOAT4 out1=bias0;\n" +" \n" +" const int in_w0_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_w1_idx_base=in_w0_idx_base+stride_hw.y;\n" +" const int in_h_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" \n" +" const int kh_start=select(0,(-in_h_idx_base+dilate_hw.x-1)/dilate_hw.x,in_h_idx_base<0);\n" +" const int in_h_idx_start=mad24(kh_start,dilate_hw.x,in_h_idx_base);\n" +" const int in_h_idx_end=min(mad24(filter_hw.x,dilate_hw.x,in_h_idx_base),in_hw.x);\n" +" \n" +" const int weight_oc_offset=out_c_blocks*filter_hw.x*filter_hw.y*4;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw.y) ? (FLOAT4)0 : vload4(in_w0_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4((in_w1_idx<0 || in_w1_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w1_idx,input+inp_offset_base));\n" +" \n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,weight+weight_offset);\n" +" char4 charWeight1=vload4(0,weight+weight_offset+weight_oc_offset);\n" +" char4 charWeight2=vload4(0,weight+weight_offset+weight_oc_offset*2);\n" +" char4 charWeight3=vload4(0,weight+weight_offset+weight_oc_offset*3);\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#else\n" +" uchar2 charWeightInt40=vload2(0,weight+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,weight+weight_offset/2+weight_oc_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,weight+weight_offset/2+weight_oc_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,weight+weight_offset/2+weight_oc_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" \n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" if(out_w_idx+1 >= out_hw.y) return;\n" +" vstore4(CONVERT_FLOAT4(out1),1,output+out_offset);\n" +"#else\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_int_c4h1w4(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#else\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=(out_c_w_idx % out_w_blocks) << 2;\n" +" const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out0=bias0;\n" +" COMPUTE_FLOAT4 out1=bias0;\n" +" COMPUTE_FLOAT4 out2=bias0;\n" +" COMPUTE_FLOAT4 out3=bias0;\n" +" const int in_w0_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_w1_idx_base=in_w0_idx_base+stride_hw.y;\n" +" const int in_w2_idx_base=in_w1_idx_base+stride_hw.y;\n" +" const int in_w3_idx_base=in_w2_idx_base+stride_hw.y;\n" +" const int in_h_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" \n" +" const int kh_start=select(0,(-in_h_idx_base+dilate_hw.x-1)/dilate_hw.x,in_h_idx_base<0);\n" +" const int in_h_idx_start=mad24(kh_start,dilate_hw.x,in_h_idx_base);\n" +" const int in_h_idx_end=min(mad24(filter_hw.x,dilate_hw.x,in_h_idx_base),in_hw.x);\n" +" \n" +" const int weight_oc_offset=out_c_blocks*filter_hw.x*filter_hw.y*4;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw.y) ? (FLOAT4)0 : vload4(in_w0_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4((in_w1_idx<0 || in_w1_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w1_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4((in_w2_idx<0 || in_w2_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w2_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=CONVERT_COMPUTE_FLOAT4((in_w3_idx<0 || in_w3_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w3_idx,input+inp_offset_base));\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,weight+weight_offset);\n" +" char4 charWeight1=vload4(0,weight+weight_offset+weight_oc_offset);\n" +" char4 charWeight2=vload4(0,weight+weight_offset+weight_oc_offset*2);\n" +" char4 charWeight3=vload4(0,weight+weight_offset+weight_oc_offset*3);\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#else\n" +" uchar2 charWeightInt40=vload2(0,weight+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,weight+weight_offset/2+weight_oc_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,weight+weight_offset/2+weight_oc_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,weight+weight_offset/2+weight_oc_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +" \n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.y-out_w_idx;\n" +" if (remain >= 4) {\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_int_c4h4w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#else\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" +" const int out_h_idx=(out_b_h_idx % out_h_blocks) << 2;\n" +" \n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out0=bias0;\n" +" COMPUTE_FLOAT4 out1=bias0;\n" +" COMPUTE_FLOAT4 out2=bias0;\n" +" COMPUTE_FLOAT4 out3=bias0;\n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h0_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" const int in_h1_idx_base=in_h0_idx_base+stride_hw.x;\n" +" const int in_h2_idx_base=in_h1_idx_base+stride_hw.x;\n" +" const int in_h3_idx_base=in_h2_idx_base+stride_hw.x;\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int weight_oc_offset=out_c_blocks*filter_hw.x*filter_hw.y*4;\n" +" const int in_hw_size=in_hw.x*in_hw.y;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw_size) ? (FLOAT4)0 : vload4(in_h0_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4((in_h1_idx<0 || in_h1_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h1_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4((in_h2_idx<0 || in_h2_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h2_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=CONVERT_COMPUTE_FLOAT4((in_h3_idx<0 || in_h3_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h3_idx+fw,input+inp_offset_base));\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,weight+weight_offset);\n" +" char4 charWeight1=vload4(0,weight+weight_offset+weight_oc_offset);\n" +" char4 charWeight2=vload4(0,weight+weight_offset+weight_oc_offset*2);\n" +" char4 charWeight3=vload4(0,weight+weight_offset+weight_oc_offset*3);\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#else\n" +" uchar2 charWeightInt40=vload2(0,weight+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,weight+weight_offset/2+weight_oc_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,weight+weight_offset/2+weight_oc_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,weight+weight_offset/2+weight_oc_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale+offset;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale+offset;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale+offset;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale+offset;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +" \n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.x-out_h_idx;\n" +" if(remain >= 4){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_int_c8h4w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#else\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" +" const int out_h_idx=(out_b_h_idx % out_h_blocks) << 2;\n" +" \n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out0=bias0;\n" +" COMPUTE_FLOAT4 out1=bias0;\n" +" COMPUTE_FLOAT4 out2=bias0;\n" +" COMPUTE_FLOAT4 out3=bias0;\n" +" COMPUTE_FLOAT4 bias1=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx+1,bias));\n" +" COMPUTE_FLOAT4 out4=bias1;\n" +" COMPUTE_FLOAT4 out5=bias1;\n" +" COMPUTE_FLOAT4 out6=bias1;\n" +" COMPUTE_FLOAT4 out7=bias1;\n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h0_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" const int in_h1_idx_base=in_h0_idx_base+stride_hw.x;\n" +" const int in_h2_idx_base=in_h1_idx_base+stride_hw.x;\n" +" const int in_h3_idx_base=in_h2_idx_base+stride_hw.x;\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int weight_oc_offset=filter_hw.x*filter_hw.y*4;\n" +" const int weight_ic_offset=out_c_blocks*weight_oc_offset;\n" +" const int in_hw_size=in_hw.x*in_hw.y;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw_size) ? (FLOAT4)0 : vload4(in_h0_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4((in_h1_idx<0 || in_h1_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h1_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4((in_h2_idx<0 || in_h2_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h2_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=CONVERT_COMPUTE_FLOAT4((in_h3_idx<0 || in_h3_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h3_idx+fw,input+inp_offset_base));\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,weight+weight_offset);\n" +" char4 charWeight1=vload4(0,weight+weight_offset+weight_ic_offset);\n" +" char4 charWeight2=vload4(0,weight+weight_offset+weight_ic_offset*2);\n" +" char4 charWeight3=vload4(0,weight+weight_offset+weight_ic_offset*3);\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale0+offset0;\n" +"#else\n" +" uchar2 charWeightInt40=vload2(0,weight+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,weight+weight_offset/2+weight_ic_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,weight+weight_offset/2+weight_ic_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,weight+weight_offset/2+weight_ic_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)- 8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale0+offset0;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" charWeight0=vload4(0,weight+weight_offset+weight_oc_offset);\n" +" charWeight1=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset);\n" +" charWeight2=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*2);\n" +" charWeight3=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*3);\n" +" weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale1+offset1;\n" +" weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale1+offset1;\n" +" weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale1+offset1;\n" +" weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale1+offset1;\n" +"#else\n" +" charWeightInt40=vload2(0,weight+weight_offset/2+weight_oc_offset/2);\n" +" charWeightInt41=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2);\n" +" charWeightInt42=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset*2/2);\n" +" charWeightInt43=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset*3/2);\n" +" charWeight0=(char4)(0,0,0,0);\n" +" charWeight1=(char4)(0,0,0,0);\n" +" charWeight2=(char4)(0,0,0,0);\n" +" charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)- 8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)- 8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale1+offset1;\n" +" weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale1+offset1;\n" +" weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale1+offset1;\n" +" weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale1+offset1;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out4=mad(in0.x,weight0,out4);\n" +" out4=mad(in0.y,weight1,out4);\n" +" out4=mad(in0.z,weight2,out4);\n" +" out4=mad(in0.w,weight3,out4);\n" +" \n" +" out5=mad(in1.x,weight0,out5);\n" +" out5=mad(in1.y,weight1,out5);\n" +" out5=mad(in1.z,weight2,out5);\n" +" out5=mad(in1.w,weight3,out5);\n" +" \n" +" out6=mad(in2.x,weight0,out6);\n" +" out6=mad(in2.y,weight1,out6);\n" +" out6=mad(in2.z,weight2,out6);\n" +" out6=mad(in2.w,weight3,out6);\n" +" \n" +" out7=mad(in3.x,weight0,out7);\n" +" out7=mad(in3.y,weight1,out7);\n" +" out7=mad(in3.z,weight2,out7);\n" +" out7=mad(in3.w,weight3,out7);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +" out4=fmax(out4,(COMPUTE_FLOAT4)0);\n" +" out5=fmax(out5,(COMPUTE_FLOAT4)0);\n" +" out6=fmax(out6,(COMPUTE_FLOAT4)0);\n" +" out7=fmax(out7,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out4=clamp(out4,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out5=clamp(out5,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out6=clamp(out6,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out7=clamp(out7,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.x-out_h_idx;\n" +" if(remain >= 4){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" if(remain >= 4){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out7),3*out_hw.y,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2*out_hw.y,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out7),3*out_hw.y,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_int_c8h2w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#else\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" +" const int out_h_idx=(out_b_h_idx % out_h_blocks) << 1;\n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out0=bias0;\n" +" COMPUTE_FLOAT4 out1=bias0;\n" +" COMPUTE_FLOAT4 bias1=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx+1,bias));\n" +" COMPUTE_FLOAT4 out2=bias1;\n" +" COMPUTE_FLOAT4 out3=bias1;\n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h0_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" const int in_h1_idx_base=in_h0_idx_base+stride_hw.x;\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int weight_oc_offset=filter_hw.x*filter_hw.y*4;\n" +" const int weight_ic_offset=out_c_blocks*weight_oc_offset;\n" +" const int in_hw_size=in_hw.x*in_hw.y;\n" +" // weight: [ic/4,oc,4],loop: ic/4\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw_size) ? (FLOAT4)0 : vload4(in_h0_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4((in_h1_idx<0 || in_h1_idx >= in_hw_size) ? (FLOAT4)0 : vload4(in_h1_idx+fw,input+inp_offset_base));\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,weight+weight_offset);\n" +" char4 charWeight1=vload4(0,weight+weight_offset+weight_ic_offset);\n" +" char4 charWeight2=vload4(0,weight+weight_offset+weight_ic_offset*2);\n" +" char4 charWeight3=vload4(0,weight+weight_offset+weight_ic_offset*3);\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale0+offset0;\n" +"#else\n" +" uchar2 charWeightInt40=vload2(0,weight+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,weight+weight_offset/2+weight_ic_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,weight+weight_offset/2+weight_ic_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,weight+weight_offset/2+weight_ic_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale0+offset0;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" charWeight0=vload4(0,weight+weight_offset+weight_oc_offset);\n" +" charWeight1=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset);\n" +" charWeight2=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*2);\n" +" charWeight3=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*3);\n" +" weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale1+offset1;\n" +" weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale1+offset1;\n" +" weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale1+offset1;\n" +" weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale1+offset1;\n" +"#else\n" +" charWeightInt40=vload2(0,weight+weight_offset/2+weight_oc_offset/2);\n" +" charWeightInt41=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2);\n" +" charWeightInt42=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset*2/2);\n" +" charWeightInt43=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset*3/2);\n" +" charWeight0=(char4)(0,0,0,0);\n" +" charWeight1=(char4)(0,0,0,0);\n" +" charWeight2=(char4)(0,0,0,0);\n" +" charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0& MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1& MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0& MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1& MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0& MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1& MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0& MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1& MOD_NUM)-8;\n" +" weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale1+offset1;\n" +" weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale1+offset1;\n" +" weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale1+offset1;\n" +" weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale1+offset1;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out2=mad(in0.x,weight0,out2);\n" +" out2=mad(in0.y,weight1,out2);\n" +" out2=mad(in0.z,weight2,out2);\n" +" out2=mad(in0.w,weight3,out2);\n" +" \n" +" out3=mad(in1.x,weight0,out3);\n" +" out3=mad(in1.y,weight1,out3);\n" +" out3=mad(in1.z,weight2,out3);\n" +" out3=mad(in1.w,weight3,out3);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.x-out_h_idx;\n" +" if(remain >= 2){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" if(remain >= 2){\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),out_hw.y,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_int_c8h1w4(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#else\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks,\n" +" __private const int blockDim) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=(out_c_w_idx % out_w_blocks) << 2;\n" +" const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" \n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out0=bias0;\n" +" COMPUTE_FLOAT4 out1=bias0;\n" +" COMPUTE_FLOAT4 out2=bias0;\n" +" COMPUTE_FLOAT4 out3=bias0;\n" +" COMPUTE_FLOAT4 bias1=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx+1,bias));\n" +" COMPUTE_FLOAT4 out4=bias1;\n" +" COMPUTE_FLOAT4 out5=bias1;\n" +" COMPUTE_FLOAT4 out6=bias1;\n" +" COMPUTE_FLOAT4 out7=bias1;\n" +" const int in_w0_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_w1_idx_base=in_w0_idx_base+stride_hw.y;\n" +" const int in_w2_idx_base=in_w1_idx_base+stride_hw.y;\n" +" const int in_w3_idx_base=in_w2_idx_base+stride_hw.y;\n" +" const int in_h_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" \n" +" const int kh_start=select(0,(-in_h_idx_base+dilate_hw.x-1)/dilate_hw.x,in_h_idx_base<0);\n" +" const int in_h_idx_start=mad24(kh_start,dilate_hw.x,in_h_idx_base);\n" +" const int in_h_idx_end=min(mad24(filter_hw.x,dilate_hw.x,in_h_idx_base),in_hw.x);\n" +" \n" +" const int weight_oc_offset=filter_hw.x*filter_hw.y*4;\n" +" const int weight_ic_offset=out_c_blocks*weight_oc_offset;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw.y) ? (FLOAT4)0 : vload4(in_w0_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=CONVERT_COMPUTE_FLOAT4((in_w1_idx<0 || in_w1_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w1_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=CONVERT_COMPUTE_FLOAT4((in_w2_idx<0 || in_w2_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w2_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=CONVERT_COMPUTE_FLOAT4((in_w3_idx<0 || in_w3_idx >= in_hw.y) ? (FLOAT4)0 : vload4(in_w3_idx,input+inp_offset_base));\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" char4 charWeight0=vload4(0,weight+weight_offset);\n" +" char4 charWeight1=vload4(0,weight+weight_offset+weight_ic_offset);\n" +" char4 charWeight2=vload4(0,weight+weight_offset+weight_ic_offset*2);\n" +" char4 charWeight3=vload4(0,weight+weight_offset+weight_ic_offset*3);\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale0+offset0;\n" +"#else\n" +" uchar2 charWeightInt40=vload2(0,weight+weight_offset/2);\n" +" uchar2 charWeightInt41=vload2(0,weight+weight_offset/2+weight_ic_offset/2);\n" +" uchar2 charWeightInt42=vload2(0,weight+weight_offset/2+weight_ic_offset*2/2);\n" +" uchar2 charWeightInt43=vload2(0,weight+weight_offset/2+weight_ic_offset*3/2);\n" +" char4 charWeight0=(char4)(0,0,0,0);\n" +" char4 charWeight1=(char4)(0,0,0,0);\n" +" char4 charWeight2=(char4)(0,0,0,0);\n" +" char4 charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)-8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale0+offset0;\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale0+offset0;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" \n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" charWeight0=vload4(0,weight+weight_offset+weight_oc_offset);\n" +" charWeight1=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset);\n" +" charWeight2=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*2);\n" +" charWeight3=vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*3);\n" +" weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale1+offset1;\n" +" weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale1+offset1;\n" +" weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale1+offset1;\n" +" weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale1+offset1;\n" +"#else\n" +" charWeightInt40=vload2(0,weight+weight_offset/2+weight_oc_offset/2);\n" +" charWeightInt41=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset/2);\n" +" charWeightInt42=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset*2/2);\n" +" charWeightInt43=vload2(0,weight+weight_offset/2+weight_oc_offset/2+weight_ic_offset*3/2);\n" +" charWeight0=(char4)(0,0,0,0);\n" +" charWeight1=(char4)(0,0,0,0);\n" +" charWeight2=(char4)(0,0,0,0);\n" +" charWeight3=(char4)(0,0,0,0);\n" +" charWeight0.x=(charWeightInt40.s0 >> 4)-8;\n" +" charWeight0.y=(charWeightInt40.s0 & MOD_NUM)-8;\n" +" charWeight0.z=(charWeightInt40.s1 >> 4)-8;\n" +" charWeight0.w=(charWeightInt40.s1 & MOD_NUM)-8;\n" +" charWeight1.x=(charWeightInt41.s0 >> 4)-8;\n" +" charWeight1.y=(charWeightInt41.s0 & MOD_NUM)- 8;\n" +" charWeight1.z=(charWeightInt41.s1 >> 4)-8;\n" +" charWeight1.w=(charWeightInt41.s1 & MOD_NUM)-8;\n" +" charWeight2.x=(charWeightInt42.s0 >> 4)-8;\n" +" charWeight2.y=(charWeightInt42.s0 & MOD_NUM)-8;\n" +" charWeight2.z=(charWeightInt42.s1 >> 4)-8;\n" +" charWeight2.w=(charWeightInt42.s1 & MOD_NUM)-8;\n" +" charWeight3.x=(charWeightInt43.s0 >> 4)-8;\n" +" charWeight3.y=(charWeightInt43.s0 & MOD_NUM)-8;\n" +" charWeight3.z=(charWeightInt43.s1 >> 4)-8;\n" +" charWeight3.w=(charWeightInt43.s1 & MOD_NUM)-8;\n" +" weight0=CONVERT_COMPUTE_FLOAT4(charWeight0)*scale1+offset1;\n" +" weight1=CONVERT_COMPUTE_FLOAT4(charWeight1)*scale1+offset1;\n" +" weight2=CONVERT_COMPUTE_FLOAT4(charWeight2)*scale1+offset1;\n" +" weight3=CONVERT_COMPUTE_FLOAT4(charWeight3)*scale1+offset1;\n" +"#endif\n" +" PADZEROSVEC(in_c_idx,inChannel,weight0,weight1,weight2,weight3);\n" +" \n" +" out4=mad(in0.x,weight0,out4);\n" +" out4=mad(in0.y,weight1,out4);\n" +" out4=mad(in0.z,weight2,out4);\n" +" out4=mad(in0.w,weight3,out4);\n" +" \n" +" out5=mad(in1.x,weight0,out5);\n" +" out5=mad(in1.y,weight1,out5);\n" +" out5=mad(in1.z,weight2,out5);\n" +" out5=mad(in1.w,weight3,out5);\n" +" \n" +" out6=mad(in2.x,weight0,out6);\n" +" out6=mad(in2.y,weight1,out6);\n" +" out6=mad(in2.z,weight2,out6);\n" +" out6=mad(in2.w,weight3,out6);\n" +" \n" +" out7=mad(in3.x,weight0,out7);\n" +" out7=mad(in3.y,weight1,out7);\n" +" out7=mad(in3.z,weight2,out7);\n" +" out7=mad(in3.w,weight3,out7);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +" out4=fmax(out4,(COMPUTE_FLOAT4)0);\n" +" out5=fmax(out5,(COMPUTE_FLOAT4)0);\n" +" out6=fmax(out6,(COMPUTE_FLOAT4)0);\n" +" out7=fmax(out7,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out4=clamp(out4,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out5=clamp(out5,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out6=clamp(out6,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out7=clamp(out7,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.y-out_w_idx;\n" +" if(remain >= 4){\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks)return;\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" if(remain >= 4){\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out4,out5,out6,out7)),0,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks)return;\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out4,out5,out6,out7)),0,output+out_offset);\n" +"#endif\n" +"}\n" +; #endif #ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "interp_buf", - { 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} - }, +const char* interp_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void nearest_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT* input,\n" +" __global FLOAT* output,\n" +" __private const float height_scale,\n" +" __private const float width_scale,\n" +" __private const float height_offset,\n" +" __private const float width_offset,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int out_height,\n" +" __private const int out_width,\n" +" __private const int channelBlocks) {\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_batch_idx=output_batch_height_block_idx/out_height;\n" +" const int output_height_idx=output_batch_height_block_idx % out_height;\n" +" const float in_h_idx=output_height_idx*height_scale+height_offset;\n" +" const float in_w_idx=output_width_block_idx*width_scale+width_offset;\n" +"#ifdef USE_ROUND\n" +" const int in_h_index=min(max(0,(int)floor(in_h_idx+0.499f)),input_height-1);\n" +" const int in_w_index=min(max(0,(int)floor(in_w_idx+0.499f)),input_width-1);\n" +"#else\n" +" const int in_h_index=min(max(0,(int)floor(in_h_idx)),input_height-1);\n" +" const int in_w_index=min(max(0,(int)floor(in_w_idx)),input_width-1);\n" +"#endif\n" +" const int inp_offset=((output_batch_idx*channelBlocks+output_channel_block_idx)*input_height+in_h_index)*input_width+in_w_index;\n" +" FLOAT4 value=vload4(inp_offset,input);\n" +" const int out_offset=((output_batch_idx*channelBlocks+output_channel_block_idx)*out_height+output_height_idx)*out_width+output_width_block_idx;\n" +" vstore4(value,out_offset,output);\n" +"}\n" +"__kernel void bilinear_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT* input,\n" +" __global FLOAT* output,\n" +" __private const float height_scale,\n" +" __private const float width_scale,\n" +" __private const float height_offset,\n" +" __private const float width_offset,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int out_height,\n" +" __private const int out_width,\n" +" __private const int channelBlocks) {\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" \n" +" const int output_batch_idx=output_batch_height_block_idx/out_height;\n" +" const int output_height_idx=output_batch_height_block_idx % out_height;\n" +" const float in_h_idx=output_height_idx*height_scale+height_offset;\n" +" const float in_w_idx=output_width_block_idx*width_scale+width_offset;\n" +" const int in_h0_index=min(max(0,(int)floor(in_h_idx)),input_height-1);\n" +" const int in_w0_index=min(max(0,(int)floor(in_w_idx)),input_width-1);\n" +" const int in_h1_index=min(max(0,(int)floor(in_h_idx)+1),input_height-1);\n" +" const int in_w1_index=min(max(0,(int)floor(in_w_idx)+1),input_width-1);\n" +" \n" +" float factor_w=(in_w_idx-(int)floor(in_w_idx));\n" +" float factor_h=(in_h_idx-(int)floor(in_h_idx));\n" +" \n" +" const int inp_offset_base=(output_batch_idx*channelBlocks+output_channel_block_idx)*input_height;\n" +" const int inp_offset_00=(inp_offset_base+in_h0_index)*input_width+in_w0_index;\n" +" const int inp_offset_01=(inp_offset_base+in_h0_index)*input_width+in_w1_index;\n" +" const int inp_offset_10=(inp_offset_base+in_h1_index)*input_width+in_w0_index;\n" +" const int inp_offset_11=(inp_offset_base+in_h1_index)*input_width+in_w1_index;\n" +" FLOAT4 value_00=vload4(inp_offset_00,input);\n" +" FLOAT4 value_01=vload4(inp_offset_01,input);\n" +" FLOAT4 value_10=vload4(inp_offset_10,input);\n" +" FLOAT4 value_11=vload4(inp_offset_11,input);\n" +" FLOAT4 value=CONVERT_FLOAT4((float4)((1.0-factor_w)*(1.0-factor_h))*convert_float4(value_00)+(float4)(factor_w*(1.0-factor_h))*convert_float4(value_01)+(float4)((1.0-factor_w)*factor_h)*convert_float4(value_10)+(float4)(factor_w*factor_h)*convert_float4(value_11));\n" +" \n" +" const int out_offset=((output_batch_idx*channelBlocks+output_channel_block_idx)*out_height+output_height_idx)*out_width+output_width_block_idx;\n" +" \n" +" vstore4(value,out_offset,output);\n" +"}\n" +"__kernel void nearest3D_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT* input,\n" +" __global FLOAT* output,\n" +" __private const float depth_scale,\n" +" __private const float height_scale,\n" +" __private const float width_scale,\n" +" __private const float depth_offset,\n" +" __private const float height_offset,\n" +" __private const float width_offset,\n" +" __private const int input_depth,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int out_depth,\n" +" __private const int out_height,\n" +" __private const int out_width,\n" +" __private const int channelBlocks) {\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_height_width_block_idx=get_global_id(1);\n" +" const int output_batch_depth_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_height_width_block_idx,output_batch_depth_block_idx);\n" +" const int output_batch_idx=output_batch_depth_block_idx/out_depth;\n" +" const int output_depth_idx=output_batch_depth_block_idx % out_depth;\n" +" const int output_height_idx=output_height_width_block_idx/out_height;\n" +" const int output_width_idx=output_height_width_block_idx % out_height;\n" +" const float in_d_idx=output_depth_idx*depth_scale+depth_offset;\n" +" const float in_h_idx=output_height_idx*height_scale+height_offset;\n" +" const float in_w_idx=output_width_idx*width_scale+width_offset;\n" +" const int in_d_index=min(max(0,(int)floor(in_d_idx)),input_depth-1);\n" +" const int in_h_index=min(max(0,(int)floor(in_h_idx)),input_height-1);\n" +" const int in_w_index=min(max(0,(int)floor(in_w_idx)),input_width-1);\n" +" const int inp_offset=(((output_batch_idx*channelBlocks+output_channel_block_idx)\n" +"*input_depth+in_d_index)*input_height+in_h_index)*input_width+in_w_index;\n" +" const int out_offset=(((output_batch_idx*channelBlocks+output_channel_block_idx)\n" +"*out_depth+output_depth_idx)*out_height+output_height_idx)*out_width+output_width_idx;\n" +" FLOAT4 value=vload4(inp_offset,input);\n" +" vstore4(value,out_offset,output);\n" +"}\n" +; #endif -{ - "scale", - { 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} - }, +const char* scale = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void scale(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__read_only image2d_t scale,\n" +"#ifdef HAS_BIAS\n" +" __read_only image2d_t bias,/* cout%4*cout/4 */\n" +"#endif\n" +" __write_only image2d_t output) {\n" +" const int channel_block_idx=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int hb=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(channel_block_idx,w,hb);\n" +" const int width=global_size_dim1;\n" +" const int pos=mad24(channel_block_idx,width,w);\n" +" FLOAT4 in=RI_F(input,SAMPLER,(int2)(pos,hb));\n" +" FLOAT4 scale_value=RI_F(scale,SAMPLER,(int2)(channel_block_idx,0));\n" +"#ifdef HAS_BIAS\n" +" FLOAT4 bias_value=RI_F(bias,SAMPLER,(int2)(channel_block_idx,0));\n" +" FLOAT4 out=in*scale_value+bias_value;\n" +"#else\n" +" FLOAT4 out=in*scale_value;\n" +"#endif\n" +" WI_F(output,(int2)(pos,hb),out);\n" +"}\n" +; +const char* softmax = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define EXP exp\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void softmax_channel(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__write_only image2d_t output,\n" +" __private const int remain_channels,__private const int4 shape // NCHW\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int bh=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(x,w,bh);\n" +"#if SOFTMAX_LOCAL_SIZE >= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT4 local sum[SOFTMAX_LOCAL_SIZE];\n" +" FLOAT4 maxValue=(FLOAT4)-FLT_MAX;\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT4 local sum[SOFTMAX_LOCAL_SIZE];\n" +" /*Compute Max */\n" +" FLOAT4 maxValue=(FLOAT4)(-FLT_MAX);\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT4 local sum[SOFTMAX_LOCAL_SIZE];\n" +" \n" +" /*Compute Max */\n" +" FLOAT4 maxValue=(FLOAT4)(-FLT_MAX);\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +"#define GLOBAL_SIZE_DIM3 "" __private int global_size_dim0,__private int global_size_dim1,__private int global_size_dim2,\n" +"#define UNIFORM_BOUNDRY_CHECK3(index0, index1, index2) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1 || index2 >= global_size_dim2) { "" return; "" }\n" +"#define UCHAR16_TO_2CHAR16(a, b, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8 = (c.s4 >> 4) - 8; a.s9 = (c.s4 & 15) - 8; a.sa = (c.s5 >> 4) - 8; a.sb = (c.s5 & 15) - 8; a.sc = (c.s6 >> 4) - 8; a.sd = (c.s6 & 15) - 8; a.se = (c.s7 >> 4) - 8; a.sf = (c.s7 & 15) - 8; "" b.s0 = (c.s8 >> 4) - 8; b.s1 = (c.s8 & 15) - 8; b.s2 = (c.s9 >> 4) - 8; b.s3 = (c.s9 & 15) - 8; b.s4 = (c.sa >> 4) - 8; b.s5 = (c.sa & 15) - 8; b.s6 = (c.sb >> 4) - 8; b.s7 = (c.sb & 15) - 8; "" b.s8=(c.sc >> 4)-8; b.s9=(c.sc & 15)-8; b.sa=(c.sd >> 4)-8; b.sb=(c.sd & 15)-8; b.sc=(c.se >> 4)-8; b.sd=(c.se & 15)-8; b.se=(c.sf >> 4)-8; b.sf=(c.sf & 15)-8;\n" +"#define UCHAR8_TO_CHAR16(a, c) "" a.s0 = (c.s0 >> 4) - 8; a.s1 = (c.s0 & 15) - 8; a.s2 = (c.s1 >> 4) - 8; a.s3 = (c.s1 & 15) - 8; a.s4 = (c.s2 >> 4) - 8; a.s5 = (c.s2 & 15) - 8; a.s6 = (c.s3 >> 4) - 8; a.s7 = (c.s3 & 15) - 8; "" a.s8=(c.s4 >> 4)-8; a.s9=(c.s4 & 15)-8; a.sa=(c.s5 >> 4)-8; a.sb=(c.s5 & 15)-8; a.sc=(c.s6 >> 4)-8; a.sd=(c.s6 & 15)-8; a.se=(c.s7 >> 4)-8; a.sf=(c.s7 & 15)-8;\n" +"#define DOT16X16(a, b, c) "" c += dot(a.s0123, b.s0123); "" c += dot(a.s4567, b.s4567); "" c += dot(a.s89ab, b.s89ab); "" c += dot(a.scdef,b.scdef);\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void reshape_nchw4_nhwc4(GLOBAL_SIZE_DIM3\n" +"__global const FLOAT* input,\n" +"__global FLOAT* output,\n" +"__private const int width_height,\n" +"__private const int batch,\n" +"__private const int channel,\n" +"__private const int channelC4){\n" +" const int x=get_global_id(0); //c\n" +" const int y=get_global_id(1); //b\n" +" const int wh=get_global_id(2); // w*h\n" +" UNIFORM_BOUNDRY_CHECK3(x,y,wh);\n" +" \n" +" const int x4=x << 2;\n" +" const int y4=y << 2;\n" +" const int channel4=channelC4*4;\n" +" const int stride=channel4*width_height;\n" +" const int input_offset=(y4*channel4+x4)*width_height+wh*4;\n" +" const int output_offset=((y*width_height+wh)*channel4+x4)*4;\n" +" FLOAT4 in0=vload4(0,input+input_offset);\n" +" FLOAT4 in1=(y4+1= channel){\n" +" FLOAT *in0_ptr=(FLOAT*)&in0;\n" +" FLOAT *in1_ptr=(FLOAT*)&in1;\n" +" FLOAT *in2_ptr=(FLOAT*)&in2;\n" +" FLOAT *in3_ptr=(FLOAT*)&in3;\n" +" int remain=x4+3-channel;\n" +" for(int i=remain; i >= 0; i--){\n" +" in0_ptr[3-remain]=0;\n" +" in1_ptr[3-remain]=0;\n" +" in2_ptr[3-remain]=0;\n" +" in3_ptr[3-remain]=0;\n" +" }\n" +" }\n" +"#endif\n" +" \n" +" FLOAT16 out=(FLOAT16)(in0.s0,in1.s0,in2.s0,in3.s0,in0.s1,in1.s1,in2.s1,in3.s1,in0.s2,in1.s2,in2.s2,in3.s2,in0.s3,in1.s3,in2.s3,in3.s3);\n" +" \n" +" vstore16(out,0,output+output_offset);\n" +"}\n" +"__kernel void reshape_nhwc4_nchw4(GLOBAL_SIZE_DIM3\n" +"__global const FLOAT* input,\n" +"__global FLOAT* output,\n" +"__private const int width_height,\n" +"__private const int batch,\n" +"__private const int channelC4){\n" +" const int x=get_global_id(0); //c\n" +" const int y=get_global_id(1); //b\n" +" const int wh=get_global_id(2); //w*h\n" +" UNIFORM_BOUNDRY_CHECK3(x,y,wh);\n" +" \n" +" const int x4=x << 2;\n" +" const int y4=y << 2;\n" +" const int channel4=channelC4*4;\n" +" const int stride=channel4*width_height;\n" +" const int input_offset=((y*width_height+wh)*channel4+x4)*4;\n" +" const int output_offset=(y4*channel4+x4)*width_height+wh*4;\n" +" FLOAT16 in=vload16(0,input+input_offset);\n" +" \n" +" FLOAT4 out0=(FLOAT4)(in.s0,in.s4,in.s8,in.sc);\n" +" FLOAT4 out1=(FLOAT4)(in.s1,in.s5,in.s9,in.sd);\n" +" FLOAT4 out2=(FLOAT4)(in.s2,in.s6,in.sa,in.se);\n" +" FLOAT4 out3=(FLOAT4)(in.s3,in.s7,in.sb,in.sf);\n" +" \n" +" vstore4(out0,0,output+output_offset);\n" +" if(y4+1 >= batch) return;\n" +" vstore4(out1,0,output+output_offset+stride);\n" +" if(y4+2 >= batch) return;\n" +" vstore4(out2,0,output+output_offset+2*stride);\n" +" if(y4+3 >= batch) return;\n" +" vstore4(out3,0,output+output_offset+3*stride);\n" +"}\n" +"__kernel void gemm_b4_c4_buf(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *weight,\n" +"#endif\n" +" __global const float *dequantScaleOffset,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT* output,\n" +" __private const int dstChannelC4,\n" +" __private const int srcChannelC4,\n" +" __private const int blockNum,\n" +" __private const int blockDim) {\n" +" const int x=get_global_id(0); //c\n" +" const int y=get_global_id(1); //b\n" +" UNIFORM_BOUNDRY_CHECK(x,y);\n" +" const int out_c_idx=x;\n" +" const int out_b_idx=y << 2;\n" +" COMPUTE_FLOAT4 bias0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out=(COMPUTE_FLOAT4)bias0.s0;\n" +" COMPUTE_FLOAT4 out1=(COMPUTE_FLOAT4)bias0.s1,out2=(COMPUTE_FLOAT4)bias0.s2,out3=(COMPUTE_FLOAT4)bias0.s3;\n" +" \n" +" int input_offset=out_b_idx*srcChannelC4*4;\n" +" int out_offset=(out_b_idx*dstChannelC4+out_c_idx*4)*4;\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" int weight_offset=out_c_idx*4*8;\n" +" int weight_oc_offset=dstChannelC4*32;\n" +"#else\n" +" int weight_offset=out_c_idx*4*16;\n" +" int weight_oc_offset=dstChannelC4*64;\n" +"#endif\n" +" const int loop=(blockDim+15)/16;\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" const int loop_end=max(loop-1,0);\n" +" const int remain=blockDim-loop_end*16;\n" +"#else\n" +" const int loop_end=loop;\n" +"#endif\n" +" \n" +" for (int i=0; i= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void buffer_set_zero(\n" +" GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(x,y);\n" +" \n" +" output[y*global_size_dim0+x]=(OUTPUT_TYPE)(0.0f);\n" +"}\n" +"__kernel void raster_buffer(\n" +" GLOBAL_SIZE_3_DIMS\n" +" __global INPUT_TYPE *input,\n" +" __private const int inputOffset,\n" +" __private const int inputStride0,\n" +" __private const int inputStride1,\n" +" __private const int inputStride2,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int outputOffset,\n" +" __private const int outputStride0,\n" +" __private const int outputStride1,\n" +" __private const int outputStride2\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" const int z=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(x,y,z);\n" +" \n" +" int inputIndex=inputOffset+z*inputStride0+y*inputStride1+x*inputStride2;\n" +" int outputIndex=outputOffset+z*outputStride0+y*outputStride1+x*outputStride2;\n" +" output[outputIndex]=(OUTPUT_TYPE)input[inputIndex];\n" +"}\n" +"__kernel void raster_nc4hw4_buffer(\n" +" GLOBAL_SIZE_3_DIMS\n" +" __global INPUT_TYPE *input,\n" +" __private const int inputOffset,\n" +" __private const int inputStride0,\n" +" __private const int inputStride1,\n" +" __private const int inputStride2,\n" +" __private const int inputHeight,\n" +" __private const int inputWidth,\n" +" __private const int inputChannel,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int outputOffset,\n" +" __private const int outputStride0,\n" +" __private const int outputStride1,\n" +" __private const int outputStride2,\n" +" __private const int outputHeight,\n" +" __private const int outputWidth,\n" +" __private const int outputChannel\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" const int z=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(x,y,z);\n" +" \n" +" int inputIndex=inputOffset+(z*inputStride0+y*inputStride1+x*inputStride2)*4;\n" +" int outputIndex=outputOffset+(z*outputStride0+y*outputStride1+x*outputStride2)*4;\n" +" \n" +" vstore4(CONVERT_OUTPUT4(vload4(0,input+inputIndex)),0,output+outputIndex);\n" +"}\n" +"__kernel void raster_direct_buffer(\n" +" GLOBAL_SIZE_3_DIMS\n" +" __private const int size_x,\n" +" __global INPUT_TYPE *input,\n" +" __private const int inputOffset,\n" +" __private const int combineSrcOffset,\n" +" __private const int inputStride0,\n" +" __private const int inputStride1,\n" +" __private const int inputStride2,\n" +" __private const int src_width,\n" +" __private const int src_height,\n" +" __private const int src_channel,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int outputOffset,\n" +" __private const int combineDstOffset,\n" +" __private const int outputStride0,\n" +" __private const int outputStride1,\n" +" __private const int outputStride2,\n" +" __private const int dst_width,\n" +" __private const int dst_height,\n" +" __private const int dst_channel\n" +" ) {\n" +" const int idx=get_global_id(0);\n" +" const int y=get_global_id(1);\n" +" const int z=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(idx,y,z);\n" +" const int x=idx % size_x;\n" +" const int id=idx/size_x;\n" +" \n" +" int inputIndex=inputOffset+id*combineSrcOffset+z*inputStride0+y*inputStride1+x*inputStride2;\n" +" int outputIndex=outputOffset+id*combineDstOffset+z*outputStride0+y*outputStride1+x*outputStride2;\n" +"#ifdef INPUT_DATA_FORMAT_NHWC\n" +" int in_c=inputIndex % src_channel; inputIndex /= src_channel;\n" +" int in_w=inputIndex % src_width; inputIndex /= src_width;\n" +" int in_h=inputIndex % src_height;\n" +" int in_b=inputIndex/src_height;\n" +" int src_channel4=(src_channel+3)/4;\n" +" int inputIndexC4=(((in_b*src_channel4+(in_c/4))*src_height+in_h)*src_width+in_w)*4+(in_c % 4);\n" +"#else\n" +" int in_w=inputIndex % src_width; inputIndex /= src_width;\n" +" int in_h=inputIndex % src_height; inputIndex /= src_height;\n" +" int in_c=inputIndex % src_channel;\n" +" int in_b=inputIndex/src_channel;\n" +" int src_channel4=(src_channel+3)/4;\n" +" int inputIndexC4=(((in_b*src_channel4+(in_c/4))*src_height+in_h)*src_width+in_w)*4+(in_c % 4);\n" +"#endif\n" +" \n" +"#ifdef OUTPUT_DATA_FORMAT_NHWC\n" +" int out_c=outputIndex % dst_channel; outputIndex /= dst_channel;\n" +" int out_w=outputIndex % dst_width; outputIndex /= dst_width;\n" +" int out_h=outputIndex % dst_height;\n" +" int out_b=outputIndex/dst_height;\n" +" int dst_channel4=(dst_channel+3)/4;\n" +" int outputIndexC4=(((out_b*dst_channel4+(out_c/4))*dst_height+out_h)*dst_width+out_w)*4+(out_c % 4);\n" +"#else\n" +" int out_w=outputIndex % dst_width; outputIndex /= dst_width;\n" +" int out_h=outputIndex % dst_height; outputIndex /= dst_height;\n" +" int out_c=outputIndex % dst_channel;\n" +" int out_b=outputIndex/dst_channel;\n" +" int dst_channel4=(dst_channel+3)/4;\n" +" int outputIndexC4=(((out_b*dst_channel4+(out_c/4))*dst_height+out_h)*dst_width+out_w)*4+(out_c % 4);\n" +"#endif\n" +" \n" +" output[outputIndexC4]=(OUTPUT_TYPE)input[inputIndexC4];\n" +"}\n" +; #endif #ifndef MNN_OPENCL_BUFFER_CLOSED #ifdef MNN_SUPPORT_INTEL_SUBGROUP -{ - "binary_subgroup_buf", - { 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} - }, +const char* binary_subgroup_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define PI 3.141592653589f\n" +"__kernel void binary_buf_c4_c4_c4(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input0,__global INPUT_TYPE* input1,__global OUTPUT_TYPE* output,\n" +" __private const int4 shape,//[N,H,W,C]\n" +" __private const int2 isFull,\n" +" __private const int activationType,\n" +" __private const int input0_pad_left,__private const int input0_pad_right,\n" +" __private const int input1_pad_left,__private const int input1_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" if (get_global_id(0) >= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int offset=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" \n" +" float4 in0=convert_float4(vload4(0,input0+offset*isFull.x));\n" +" float4 in1=convert_float4(vload4(0,input1+offset*isFull.y));\n" +" if(isFull.x == 0) {\n" +" in0=(float4)(in0.x,in0.x,in0.x,in0.x);\n" +" }\n" +" if(isFull.y == 0) {\n" +" in1=(float4)(in1.x,in1.x,in1.x,in1.x);\n" +" }\n" +" \n" +" float4 out=OPERATOR;\n" +" \n" +" if(activationType == 1) {\n" +" out=fmax(out,(float4)0);\n" +" }\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset);\n" +"}\n" +"__kernel void binary_buf_c4_c4_c16(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input0,__global INPUT_TYPE* input1,__global OUTPUT_TYPE* output,\n" +" __private const int4 shape,//[N,H,W,C]\n" +" __private const int2 isFull,\n" +" __private const int activationType,\n" +" __private const int input0_pad_left,__private const int input0_pad_right,\n" +" __private const int input1_pad_left,__private const int input1_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" if (get_global_id(0) >= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int channel16=(shape.w+15)/16;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int dst_width=shape.z+output_pad_left+output_pad_right;\n" +" const int channe_out_idx=channel_idx >> 2;\n" +" const int offset=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int dst_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width+w_idx+output_pad_left)*16+(channel_idx % 4)*4;\n" +" \n" +" float4 in0=convert_float4(vload4(0,input0+offset*isFull.x));\n" +" float4 in1=convert_float4(vload4(0,input1+offset*isFull.y));\n" +" if(isFull.x == 0) {\n" +" in0=(float4)(in0.x,in0.x,in0.x,in0.x);\n" +" }\n" +" if(isFull.y == 0) {\n" +" in1=(float4)(in1.x,in1.x,in1.x,in1.x);\n" +" }\n" +" float4 out=OPERATOR;\n" +" if(activationType == 1) {\n" +" out=fmax(out,(float4)0);\n" +" }\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+dst_offset);\n" +" if(w_idx == 0){\n" +" int pad_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width)*16+(channel_idx % 4)*4;\n" +" for(int i=0; i= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int channel16=(shape.w+15)/16;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int src_width=shape.z+input1_pad_left+input1_pad_right;\n" +" const int channe_out_idx=channel_idx >> 2;\n" +" const int offset0=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int offset1=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*src_width+w_idx+input1_pad_left)*16+(channel_idx % 4)*4;\n" +" float4 in0=convert_float4(vload4(0,input0+offset0*isFull.x));\n" +" float4 in1=convert_float4(vload4(0,input1+offset1*isFull.y));\n" +" if(isFull.x == 0) {\n" +" in0=(float4)(in0.x,in0.x,in0.x,in0.x);\n" +" }\n" +" if(isFull.y == 0) {\n" +" in1=(float4)(in1.x,in1.x,in1.x,in1.x);\n" +" }\n" +" float4 out=OPERATOR;\n" +" if(activationType == 1) {\n" +" out=fmax(out,(float4)0);\n" +" }\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset0);\n" +"}\n" +"__kernel void binary_buf_c16_c4_c4(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input0,__global INPUT_TYPE* input1,__global OUTPUT_TYPE* output,\n" +" __private const int4 shape,//[N,H,W,C]\n" +" __private const int2 isFull,\n" +" __private const int activationType,\n" +" __private const int input0_pad_left,__private const int input0_pad_right,\n" +" __private const int input1_pad_left,__private const int input1_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" if (get_global_id(0) >= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int channel16=(shape.w+15)/16;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int src_width=shape.z+input0_pad_left+input0_pad_right;\n" +" const int channe_out_idx=channel_idx >> 2;\n" +" const int offset1=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int offset0=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*src_width+w_idx+input0_pad_left)*16+(channel_idx % 4)*4;\n" +" \n" +" float4 in0=convert_float4(vload4(0,input0+offset0*isFull.x));\n" +" float4 in1=convert_float4(vload4(0,input1+offset1*isFull.y));\n" +" if(isFull.x == 0) {\n" +" in0=(float4)(in0.x,in0.x,in0.x,in0.x);\n" +" }\n" +" if(isFull.y == 0) {\n" +" in1=(float4)(in1.x,in1.x,in1.x,in1.x);\n" +" }\n" +" float4 out=OPERATOR;\n" +" \n" +" if(activationType == 1) {\n" +" out=fmax(out,(float4)0);\n" +" }\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset1);\n" +"}\n" +"__kernel void binary_buf_c4_c16_c16(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input0,__global INPUT_TYPE* input1,__global OUTPUT_TYPE* output,\n" +" __private const int4 shape,//[N,H,W,C]\n" +" __private const int2 isFull,\n" +" __private const int activationType,\n" +" __private const int input0_pad_left,__private const int input0_pad_right,\n" +" __private const int input1_pad_left,__private const int input1_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" if (get_global_id(0) >= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int channel16=(shape.w+15)/16;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int src_width=shape.z+input1_pad_left+input1_pad_right;\n" +" const int dst_width=shape.z+output_pad_left+output_pad_right;\n" +" const int channe_out_idx=channel_idx >> 2;\n" +" const int offset0=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int offset1=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*src_width+w_idx+input1_pad_left)*16+(channel_idx % 4)*4;\n" +" const int dst_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width+w_idx+output_pad_left)*16+(channel_idx % 4)*4;\n" +" \n" +" float4 in0=convert_float4(vload4(0,input0+offset0*isFull.x));\n" +" float4 in1=convert_float4(vload4(0,input1+offset1*isFull.y));\n" +" if(isFull.x == 0) {\n" +" in0=(float4)(in0.x,in0.x,in0.x,in0.x);\n" +" }\n" +" if(isFull.y == 0) {\n" +" in1=(float4)(in1.x,in1.x,in1.x,in1.x);\n" +" }\n" +" float4 out=OPERATOR;\n" +" \n" +" if(activationType == 1) {\n" +" out=fmax(out,(float4)0);\n" +" }\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+dst_offset);\n" +" if(w_idx == 0){\n" +" int pad_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width)*16+(channel_idx % 4)*4;\n" +" for(int i=0; i= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int channel16=(shape.w+15)/16;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int src_width=shape.z+input0_pad_left+input0_pad_right;\n" +" const int dst_width=shape.z+output_pad_left+output_pad_right;\n" +" const int channe_out_idx=channel_idx >> 2;\n" +" const int offset1=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int offset0=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*src_width+w_idx+input0_pad_left)*16+(channel_idx % 4)*4;\n" +" const int dst_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width+w_idx+output_pad_left)*16+(channel_idx % 4)*4;\n" +" \n" +" float4 in0=convert_float4(vload4(0,input0+offset0*isFull.x));\n" +" float4 in1=convert_float4(vload4(0,input1+offset1*isFull.y));\n" +" if(isFull.x == 0) {\n" +" in0=(float4)(in0.x,in0.x,in0.x,in0.x);\n" +" }\n" +" if(isFull.y == 0) {\n" +" in1=(float4)(in1.x,in1.x,in1.x,in1.x);\n" +" }\n" +" float4 out=OPERATOR;\n" +" \n" +" if(activationType == 1) {\n" +" out=fmax(out,(float4)0);\n" +" }\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+dst_offset);\n" +" if(w_idx == 0){\n" +" int pad_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width)*16+(channel_idx % 4)*4;\n" +" for(int i=0; i= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" \n" +" const int offset0=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int offset1=channel_idx*4;\n" +" \n" +" float4 in0=convert_float4(vload4(0,input0+offset0));\n" +" float4 in1=convert_float4(vload4(0,input1+offset1));\n" +" float4 out=OPERATOR;\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset0);\n" +"}\n" +"__kernel void prelu_buf_c4_c16(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input0,__global INPUT_TYPE* input1,__global OUTPUT_TYPE* output,\n" +" __private const int4 shape,//[N,H,W,C]\n" +" __private const int input0_pad_left,__private const int input0_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right\n" +" ) {\n" +" if (get_global_id(0) >= global_dim0 || get_global_id(1) >= global_dim1 || get_global_id(2) >= global_dim2) \n" +" return;\n" +" const int channel4=(shape.w+3)/4;\n" +" const int channel16=(shape.w+15)/16;\n" +" const int w_idx=get_global_id(0) % shape.z;\n" +" const int h_idx=get_global_id(0)/shape.z;\n" +" const int batch_idx=get_global_id(2);\n" +" const int channel_idx=get_global_id(1);\n" +" const int dst_width=shape.z+output_pad_left+output_pad_right;\n" +" const int channe_out_idx=channel_idx >> 2;\n" +" \n" +" const int offset0=(((batch_idx*channel4+channel_idx)*shape.y+h_idx)*shape.z+w_idx)*4;\n" +" const int offset1=channel_idx*4;\n" +" const int offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width+w_idx+output_pad_left)*16+(channel_idx % 4)*4;\n" +" float4 in0=convert_float4(vload4(0,input0+offset0));\n" +" float4 in1=convert_float4(vload4(0,input1+offset1));\n" +" float4 out=OPERATOR;\n" +" \n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset);\n" +" if(w_idx == 0){\n" +" int pad_offset=(((batch_idx*channel16+channe_out_idx)*shape.y+h_idx)*dst_width)*16+(channel_idx % 4)*4;\n" +" for(int i=0; ishape.z) {\n" +" for (int i=0; ishape.z ? (shape.z % 4) : 4;\n" +" for (int i=0; ishape.z) {\n" +" for (int i=0; ishape.z ? (shape.z % 4) : 4;\n" +" for (int i=0; i= inputHeight)\n" +" continue;\n" +" for(int j=0; j= inputHeight)\n" +" continue;\n" +" for(int j=0; j= inputHeight)\n" +" continue;\n" +" for(int j=0; j= inputHeight)\n" +" continue;\n" +" for(int j=0; j= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void interp(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__write_only image2d_t output,\n" +" __private const float height_scale,__private const float width_scale,\n" +" __private const float height_offset,__private const float width_offset,\n" +" __private const int input_height,__private const int input_width,\n" +" __private const int out_height) {\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_channel_block_idxs=global_size_dim0;\n" +" const int output_width=global_size_dim1;\n" +" const int output_batch_idx=output_batch_height_block_idx/out_height;\n" +" const int output_height_idx=output_batch_height_block_idx % out_height;\n" +" const float scale_height=output_height_idx*height_scale+height_offset;\n" +" const float scale_width=output_width_block_idx*width_scale+width_offset;\n" +"#ifdef USE_ROUND\n" +" const int height_lf=min(max(0,(int)floor(scale_height+0.499f)),input_height-1);\n" +" const int width_lf=min(max(0,(int)floor(scale_width+0.499f)),input_width-1);\n" +"#else\n" +" const int height_lf=min(max(0,(int)floor(scale_height)),input_height-1);\n" +" const int width_lf=min(max(0,(int)floor(scale_width)),input_width-1);\n" +"#endif\n" +" const int input_width_offset=mul24(output_channel_block_idx,input_width);\n" +" const int input_height_offset=mul24(output_batch_idx,input_height);\n" +" float4 out =\n" +" read_imagef(input,SAMPLER,(int2)(input_width_offset+width_lf,input_height_offset+height_lf));\n" +" const int out_image_w=mad24(output_channel_block_idx,output_width,output_width_block_idx);\n" +" const int out_image_h=mad24(output_batch_idx,out_height,output_height_idx);\n" +" write_imagef(output,(int2)(out_image_w,out_image_h),out);\n" +"}\n" +"__kernel void interp3D(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__write_only image2d_t output,\n" +" __private const float depth_scale,__private const float height_scale,__private const float width_scale,\n" +" __private const float depth_offset,__private const float height_offset,__private const float width_offset,\n" +" __private const int input_depth,__private const int input_height,__private const int input_width,\n" +" __private const int out_depth,__private const int out_height) {\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_height_width_block_idx=get_global_id(1);\n" +" const int output_batch_depth_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_height_width_block_idx,output_batch_depth_block_idx);\n" +" const int output_channel_block_idxs=global_size_dim0;\n" +" const int output_tensor_height_width=global_size_dim1;\n" +" const int out_width=output_tensor_height_width/out_height;\n" +" const int output_batch_idx=output_batch_depth_block_idx/out_depth;\n" +" const int output_depth_idx=output_batch_depth_block_idx % out_depth;\n" +" const int output_height_idx=output_height_width_block_idx/out_height;\n" +" const int output_width_idx=output_height_width_block_idx % out_height;\n" +" const float scale_depth=output_depth_idx*depth_scale+depth_offset;\n" +" const float scale_height=output_height_idx*height_scale+height_offset;\n" +" const float scale_width=output_width_idx*width_scale+width_offset;\n" +" const int depth_lf=max(0,(int)floor(scale_depth));\n" +" const int height_lf=max(0,(int)floor(scale_height));\n" +" const int width_lf=max(0,(int)floor(scale_width));\n" +" const int input_tensor_width_height=mul24(input_width,input_height);\n" +" const int input_image_width_offset=mul24(output_channel_block_idx,input_tensor_width_height);\n" +" const int input_image_height_offset=mul24(output_batch_idx,input_depth);\n" +" float4 out=read_imagef(input,SAMPLER,\n" +" (int2)(input_image_width_offset+input_width*(height_offset+height_lf)+width_lf+width_offset,\n" +" input_image_height_offset+depth_lf+depth_offset));\n" +" const int output_image_width_offset=output_channel_block_idx*output_tensor_height_width;\n" +" const int output_image_height_offset=output_batch_idx*out_depth;\n" +" // TODO: out\n" +" const int out_image_w=output_image_width_offset+output_height_idx*out_width+output_width_idx;\n" +" const int out_image_h=output_image_height_offset+output_batch_idx*out_depth+output_depth_idx;\n" +" write_imagef(output,(int2)(out_image_w,out_image_h),out);\n" +"}\n" +; #ifndef MNN_OPENCL_BUFFER_CLOSED #ifdef MNN_SUPPORT_INTEL_SUBGROUP -{ - "pooling_subgroup_buf", - { 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} - }, +const char* pooling_subgroup_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void pooling_c4_c4(GLOBAL_SIZE_3_DIMS __global const FLOAT *input,\n" +" __private const int2 input_shape,\n" +" __private const int2 output_shape,\n" +" __private const int2 pad_shape,\n" +" __global FLOAT *output,\n" +" __global FLOAT *rediceOutput,\n" +" __private const int channel,\n" +" __private const int in_channel_block,\n" +" __private const int out_channel_block,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right) {\n" +" \n" +" const int ow_idx=get_global_id(0);\n" +" const int b_oh_idx=get_global_id(1);\n" +" const int c_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(ow_idx,b_oh_idx,c_idx);\n" +" \n" +" const int b_idx=b_oh_idx/output_shape.x;\n" +" const int oh_idx=b_oh_idx % output_shape.x;\n" +" const int iw_start=mad24(ow_idx,STRIDE_X,-pad_shape.y);\n" +" const int ih_start=mad24(oh_idx,STRIDE_Y,-pad_shape.x);\n" +" \n" +" #ifdef POOL_AVG\n" +" COMPUTE_FLOAT4 result=(COMPUTE_FLOAT4)(0);\n" +" const int inp_offset=(((b_idx*in_channel_block+c_idx)*input_shape.x+ih_start)*input_shape.y+iw_start+input_pad_left)*4;\n" +"#ifdef COUNT_INCLUDE_PADDING\n" +" int total_count=(min(ih_start+KERNEL_Y,input_shape.x+pad_shape.x)-ih_start)*(min(iw_start+KERNEL_X,input_shape.y+pad_shape.y)-iw_start);\n" +"#else\n" +" int total_count=0;\n" +"#endif\n" +" for(int kh=0; kh= input_shape.x) {\n" +" continue;\n" +" }\n" +" for(int kw=0; kw= input_shape.y) {\n" +" continue;\n" +" }\n" +" COMPUTE_FLOAT4 inp_data=CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset+(kh*input_shape.y+kw)*4));\n" +" result += inp_data;\n" +"#ifndef COUNT_INCLUDE_PADDING\n" +" total_count++;\n" +"#endif\n" +" }\n" +" }\n" +" result=result/(COMPUTE_FLOAT4)(1.0*total_count);\n" +" #else\n" +" COMPUTE_FLOAT4 result=(COMPUTE_FLOAT4)(-FLT_MAX);\n" +" #if RETURN_REDICE\n" +" int4 redice=(int4)0;\n" +" #endif\n" +" const int inp_offset=(((b_idx*in_channel_block+c_idx)*input_shape.x+ih_start)*input_shape.y+iw_start+input_pad_left)*4;\n" +" for(int kh=0; kh= input_shape.x) {\n" +" continue;\n" +" }\n" +" for(int kw=0; kw= input_shape.y) {\n" +" continue;\n" +" }\n" +" COMPUTE_FLOAT4 inp_data=CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset+(kh*input_shape.y+kw)*4));\n" +" #if RETURN_REDICE\n" +" redice=inp_data>result ? (int4)((ih_start+kh)*input_shape.y+iw_start+kw) : redice;\n" +" #endif\n" +" result=fmax(result,inp_data);\n" +" }\n" +" }\n" +" #endif\n" +" \n" +" const int out_offset=(((b_idx*in_channel_block+c_idx)*output_shape.x+oh_idx)* output_shape.y+ow_idx+output_pad_left)*4;\n" +" vstore4(CONVERT_FLOAT4(result),0,output+out_offset);\n" +" #if RETURN_REDICE\n" +" vstore4(CONVERT_FLOAT4(redice),0,rediceOutput+(((b_idx*in_channel_block+c_idx)*output_shape.x+oh_idx)* output_shape.y+ow_idx)*4);\n" +" #endif\n" +"}\n" +"__kernel void pooling_c4_c16(GLOBAL_SIZE_3_DIMS __global const FLOAT *input,\n" +" __private const int2 input_shape,\n" +" __private const int2 output_shape,\n" +" __private const int2 pad_shape,\n" +" __global FLOAT *output,\n" +" __global FLOAT *rediceOutput,\n" +" __private const int channel,\n" +" __private const int in_channel_block,\n" +" __private const int out_channel_block,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right) {\n" +" \n" +" const int ow_idx=get_global_id(0);\n" +" const int b_oh_idx=get_global_id(1);\n" +" const int c_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(ow_idx,b_oh_idx,c_idx);\n" +" \n" +" const int b_idx=b_oh_idx/output_shape.x;\n" +" const int oh_idx=b_oh_idx % output_shape.x;\n" +" const int iw_start=mad24(ow_idx,STRIDE_X,-pad_shape.y);\n" +" const int ih_start=mad24(oh_idx,STRIDE_Y,-pad_shape.x);\n" +" const int dst_width=output_shape.y+output_pad_left+output_pad_right;\n" +" \n" +" #ifdef POOL_AVG\n" +" COMPUTE_FLOAT4 result=(COMPUTE_FLOAT4)(0);\n" +" const int inp_offset=(((b_idx*in_channel_block+c_idx)*input_shape.x+ih_start)*input_shape.y+iw_start+input_pad_left)*4;\n" +" #ifdef COUNT_INCLUDE_PADDING\n" +" int total_count=(min(ih_start+KERNEL_Y,input_shape.x+pad_shape.x)-ih_start)*(min(iw_start+KERNEL_X,input_shape.y+pad_shape.y)-iw_start);\n" +"#else\n" +" int total_count=0;\n" +"#endif\n" +" for(int kh=0; kh= input_shape.x) {\n" +" continue;\n" +" }\n" +" for(int kw=0; kw= input_shape.y) {\n" +" continue;\n" +" }\n" +" COMPUTE_FLOAT4 inp_data=CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset+(kh*input_shape.y+kw)*4));\n" +" result += inp_data;\n" +"#ifndef COUNT_INCLUDE_PADDING\n" +" total_count++;\n" +"#endif\n" +" }\n" +" }\n" +" result=result/(COMPUTE_FLOAT4)(1.0*total_count);\n" +" #else\n" +" COMPUTE_FLOAT4 result=(COMPUTE_FLOAT4)(-FLT_MAX);\n" +" #if RETURN_REDICE\n" +" int4 redice=(int4)0;\n" +" #endif\n" +" const int inp_offset=(((b_idx*in_channel_block+c_idx)*input_shape.x+ih_start)*input_shape.y+iw_start+input_pad_left)*4;\n" +" for(int kh=0; kh= input_shape.x) {\n" +" continue;\n" +" }\n" +" for(int kw=0; kw= input_shape.y) {\n" +" continue;\n" +" }\n" +" COMPUTE_FLOAT4 inp_data=CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset+(kh*input_shape.y+kw)*4));\n" +" #if RETURN_REDICE\n" +" redice=inp_data>result ? (int4)((ih_start+kh)*input_shape.y+iw_start+kw) : redice;\n" +" #endif\n" +" result=fmax(result,inp_data);\n" +" }\n" +" }\n" +" #endif\n" +" const int c_left=(c_idx % 4)*4;\n" +" const int out_offset=(((b_idx*out_channel_block+c_idx/4)*output_shape.x+oh_idx)* dst_width+ow_idx+output_pad_left)*16+c_left;\n" +" vstore4(CONVERT_FLOAT4(result),0,output+out_offset);\n" +" #if RETURN_REDICE\n" +" vstore4(CONVERT_FLOAT4(redice),0,rediceOutput+(((b_idx*out_channel_block+c_idx)*output_shape.x+oh_idx)* output_shape.y+ow_idx)*4);\n" +" #endif\n" +" if(ow_idx == 0){\n" +" int pad_offset=(((b_idx*out_channel_block+c_idx/4)*output_shape.x+oh_idx)* dst_width+0)*16+c_left;\n" +" for(int i=0; i= input_shape.x) {\n" +" continue;\n" +" }\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" for (int i=0; i= 0 && (iw_start+i)result ? (int8)((ih_start+kh)*input_shape.y+iw_start+kw) : redice;\n" +"#endif\n" +" result=fmax(result,src);\n" +"#endif\n" +" }\n" +" }\n" +"#ifdef POOL_AVG\n" +" result=result/total_count;\n" +"#endif\n" +" if(ow_idx == 0){\n" +" int pad_offset=(((b_idx*out_channel_block+c_idx)*output_shape.x+oh_idx)* dst_width+0)*16+sglid;\n" +" for(int i=0; i= channel) {\n" +" for (int i=0; i<8; i++) {\n" +" if ((c_idx*16+sglid= channel) {\n" +" for (int i=0; i<8; i++) {\n" +" if ((c_idx*16+lid_y*4+lid_x= input_shape.x) {\n" +" continue;\n" +" }\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" for (int i=0; i= 0 && (iw_start+i)result ? (int8)((ih_start+kh)*input_shape.y+iw_start+kw) : redice;\n" +"#endif\n" +" result=fmax(result,src);\n" +"#endif\n" +" }\n" +" }\n" +"#ifdef POOL_AVG\n" +" result=result/total_count;\n" +"#endif\n" +" const uint lid_x=sglid % 4;\n" +" const uint lid_y=sglid/4;\n" +" \n" +" const int out_offset=(((b_idx*out_channel_block+c_idx*4)*output_shape.x+oh_idx)* output_shape.y+ow_idx+output_pad_left)*4;\n" +" const int width_height=output_shape.y*output_shape.x*4;\n" +"#if RETURN_REDICE\n" +" const int redice_offset=(((b_idx*out_channel_block+c_idx*4)*output_shape.x+oh_idx)* output_shape.y+ow_idx)*4;\n" +"#endif\n" +"#if OUTPUT_LEFTOVERS\n" +" if ((c_idx+1)*16 >= channel) {\n" +" for (int i=0; i<8; i++) {\n" +" if ((c_idx*16+lid_y*4+lid_x= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void pooling(GLOBAL_SIZE_3_DIMS __global const FLOAT *input,\n" +" __private const int2 input_shape,\n" +" __private const int2 output_shape,\n" +" __private const int2 pad_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 kernel_shape,\n" +" __global FLOAT *output,\n" +" __global FLOAT *rediceOutput,\n" +" __private const int channel_block) {\n" +" \n" +" const int ow_idx=get_global_id(0);\n" +" const int b_oh_idx=get_global_id(1);\n" +" const int c_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(ow_idx,b_oh_idx,c_idx);\n" +" \n" +" const int b_idx=b_oh_idx/output_shape.x;\n" +" const int oh_idx=b_oh_idx % output_shape.x;\n" +" const int iw_start=mad24(ow_idx,stride_shape.y,-pad_shape.y);\n" +" const int ih_start=mad24(oh_idx,stride_shape.x,-pad_shape.x);\n" +" \n" +" #ifdef POOL_AVG\n" +" COMPUTE_FLOAT4 result=(COMPUTE_FLOAT4)(0);\n" +" const int inp_offset=(((b_idx*channel_block+c_idx)*input_shape.x+ih_start)*input_shape.y+iw_start)*4;\n" +" #ifdef COUNT_INCLUDE_PADDING\n" +" int total_count=(min(ih_start+kernel_shape.x,input_shape.x+pad_shape.x)-ih_start)*(min(iw_start+kernel_shape.y,input_shape.y+pad_shape.y)-iw_start);\n" +" #else\n" +" int total_count=0;\n" +" #endif\n" +" for(int kh=0; kh= input_shape.x) {\n" +" continue;\n" +" }\n" +" for(int kw=0; kw= input_shape.y) {\n" +" continue;\n" +" }\n" +" COMPUTE_FLOAT4 inp_data=CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset+(kh*input_shape.y+kw)*4));\n" +" result += inp_data;\n" +" #ifndef COUNT_INCLUDE_PADDING\n" +" total_count++;\n" +" #endif\n" +" }\n" +" }\n" +" result=result/(COMPUTE_FLOAT4)(1.0*total_count);\n" +" #else\n" +" COMPUTE_FLOAT4 result=(COMPUTE_FLOAT4)(-FLT_MAX);\n" +" #if RETURN_REDICE\n" +" int4 redice=(int4)0;\n" +" #endif\n" +" const int inp_offset=(((b_idx*channel_block+c_idx)*input_shape.x+ih_start)*input_shape.y+iw_start)*4;\n" +" for(int kh=0; kh= input_shape.x) {\n" +" continue;\n" +" }\n" +" for(int kw=0; kw= input_shape.y) {\n" +" continue;\n" +" }\n" +" COMPUTE_FLOAT4 inp_data=CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset+(kh*input_shape.y+kw)*4));\n" +" #if RETURN_REDICE\n" +" redice=inp_data>result ? (int4)((ih_start+kh)*input_shape.y+iw_start+kw) : redice;\n" +" #endif\n" +" result=fmax(result,inp_data);\n" +" }\n" +" }\n" +" #endif\n" +" \n" +" const int out_offset=(((b_idx*channel_block+c_idx)*output_shape.x+oh_idx)* output_shape.y+ow_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(result),0,output+out_offset);\n" +" #if RETURN_REDICE\n" +" vstore4(CONVERT_FLOAT4(redice),0,rediceOutput+out_offset);\n" +" #endif\n" +"}\n" +"#ifdef LOCAL_SIZE\n" +"__kernel void global_pooling_buf(GLOBAL_SIZE_3_DIMS __global const FLOAT *input,\n" +" __private const int2 input_shape,\n" +" __private const int2 output_shape,\n" +" __private const int2 pad_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 kernel_shape,\n" +" __global FLOAT *output,\n" +" __global FLOAT *rediceOutput,\n" +" __private const int channel_block) {\n" +" const int local_id=get_local_id(0);\n" +" const int output_channel_idx=get_global_id(1);\n" +" const int output_batch_idx=get_global_id(2);\n" +"#ifdef POOL_AVG\n" +" COMPUTE_FLOAT4 output_result=0;\n" +"#else\n" +" COMPUTE_FLOAT4 output_result=(COMPUTE_FLOAT4)(-FLT_MAX);\n" +"#if RETURN_REDICE\n" +" int4 redice=(int4)0;\n" +" int4 local rediceId[LOCAL_SIZE];\n" +"#endif\n" +"#endif\n" +" COMPUTE_FLOAT4 local sum[LOCAL_SIZE];\n" +" const int inp_offset=((output_batch_idx*channel_block+output_channel_idx)*input_shape.x)*input_shape.y*4;\n" +" const int size=input_shape.x*input_shape.y;\n" +" for(int i=local_id; ioutput_result ? (int4)(i) : redice;\n" +"#endif\n" +"#endif\n" +" }\n" +" \n" +" sum[local_id]=output_result;\n" +"#if RETURN_REDICE\n" +" rediceId[local_id]=redice;\n" +"#endif\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (local_idsum[local_id+i] ? rediceId[local_id] : rediceId[local_id+i];\n" +"#endif\n" +" }\n" +"#endif\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" }\n" +" output_result=sum[0];\n" +"#ifdef POOL_AVG\n" +" output_result /= (input_shape.x*input_shape.y);\n" +"#endif\n" +" const int out_offset=(output_batch_idx*channel_block+output_channel_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(output_result),0,output+out_offset);\n" +"#if RETURN_REDICE\n" +" redice=rediceId[0];\n" +" vstore4(CONVERT_FLOAT4(redice),0,rediceOutput+out_offset);\n" +"#endif\n" +"}\n" +"#endif\n" +; #endif -{ - "winogradTransformSource2_5_1", - { 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} - }, +const char* winogradTransformSource2_5_1 = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void winogradTransformSource(__read_only image2d_t uInput,// 0\n" +" __write_only image2d_t uOutput,__private const int unitWidth,\n" +" __private const int unitHeight,// 3\n" +" __private const int padX,__private const int padY,\n" +" __private const int srcWidth,// 6\n" +" __private const int srcHeight,__private const int srcChannelC4,\n" +" __private const int batchOffset) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1)); \n" +" if (pos.x= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S00=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S10=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S20=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S30=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=4+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S40=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=5+sxStart;\n" +" int sy=0+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S50=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S01=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S11=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S21=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S31=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=4+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S41=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=5+sxStart;\n" +" int sy=1+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S51=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S02=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S12=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S22=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S32=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=4+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S42=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=5+sxStart;\n" +" int sy=2+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S52=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S03=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S13=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S23=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S33=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=4+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S43=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=5+sxStart;\n" +" int sy=3+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S53=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=4+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S04=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=4+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S14=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=4+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S24=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=4+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S34=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=4+sxStart;\n" +" int sy=4+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S44=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=5+sxStart;\n" +" int sy=4+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S54=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=5+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S05=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=5+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S15=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=5+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S25=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=5+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S35=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=4+sxStart;\n" +" int sy=5+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S45=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" {\n" +" int sx=5+sxStart;\n" +" int sy=5+syStart;\n" +" int imageSx=select(sx+pos.y*srcWidth,-1,sx<0 || sx >= srcWidth);\n" +" int imageSy=select(batchOffset*srcHeight+sy,-1,sy<0 || sy >= srcHeight);\n" +" S55=RI_F(uInput,SAMPLER,(int2)(imageSx,imageSy));\n" +" }\n" +" FLOAT4 m00=+S00-(FLOAT)1.25*S02+(FLOAT)0.25*S04;\n" +" FLOAT4 m10=+S10-(FLOAT)1.25*S12+(FLOAT)0.25*S14;\n" +" FLOAT4 m20=+S20-(FLOAT)1.25*S22+(FLOAT)0.25*S24;\n" +" FLOAT4 m30=+S30-(FLOAT)1.25*S32+(FLOAT)0.25*S34;\n" +" FLOAT4 m40=+S40-(FLOAT)1.25*S42+(FLOAT)0.25*S44;\n" +" FLOAT4 m50=+S50-(FLOAT)1.25*S52+(FLOAT)0.25*S54;\n" +" FLOAT4 m01=+(FLOAT)0.666667*S01+(FLOAT)0.666667*S02-(FLOAT)0.166667*S03-(FLOAT)0.166667*S04;\n" +" FLOAT4 m11=+(FLOAT)0.666667*S11+(FLOAT)0.666667*S12-(FLOAT)0.166667*S13-(FLOAT)0.166667*S14;\n" +" FLOAT4 m21=+(FLOAT)0.666667*S21+(FLOAT)0.666667*S22-(FLOAT)0.166667*S23-(FLOAT)0.166667*S24;\n" +" FLOAT4 m31=+(FLOAT)0.666667*S31+(FLOAT)0.666667*S32-(FLOAT)0.166667*S33-(FLOAT)0.166667*S34;\n" +" FLOAT4 m41=+(FLOAT)0.666667*S41+(FLOAT)0.666667*S42-(FLOAT)0.166667*S43-(FLOAT)0.166667*S44;\n" +" FLOAT4 m51=+(FLOAT)0.666667*S51+(FLOAT)0.666667*S52-(FLOAT)0.166667*S53-(FLOAT)0.166667*S54;\n" +" FLOAT4 m02=-(FLOAT)0.666667*S01+(FLOAT)0.666667*S02+(FLOAT)0.166667*S03-(FLOAT)0.166667*S04;\n" +" FLOAT4 m12=-(FLOAT)0.666667*S11+(FLOAT)0.666667*S12+(FLOAT)0.166667*S13-(FLOAT)0.166667*S14;\n" +" FLOAT4 m22=-(FLOAT)0.666667*S21+(FLOAT)0.666667*S22+(FLOAT)0.166667*S23-(FLOAT)0.166667*S24;\n" +" FLOAT4 m32=-(FLOAT)0.666667*S31+(FLOAT)0.666667*S32+(FLOAT)0.166667*S33-(FLOAT)0.166667*S34;\n" +" FLOAT4 m42=-(FLOAT)0.666667*S41+(FLOAT)0.666667*S42+(FLOAT)0.166667*S43-(FLOAT)0.166667*S44;\n" +" FLOAT4 m52=-(FLOAT)0.666667*S51+(FLOAT)0.666667*S52+(FLOAT)0.166667*S53-(FLOAT)0.166667*S54;\n" +" FLOAT4 m03 =\n" +" -(FLOAT)0.0833333*S01-(FLOAT)0.0416667*S02+(FLOAT)0.0833333*S03+(FLOAT)0.0416667*S04;\n" +" FLOAT4 m13 =\n" +" -(FLOAT)0.0833333*S11-(FLOAT)0.0416667*S12+(FLOAT)0.0833333*S13+(FLOAT)0.0416667*S14;\n" +" FLOAT4 m23 =\n" +" -(FLOAT)0.0833333*S21-(FLOAT)0.0416667*S22+(FLOAT)0.0833333*S23+(FLOAT)0.0416667*S24;\n" +" FLOAT4 m33 =\n" +" -(FLOAT)0.0833333*S31-(FLOAT)0.0416667*S32+(FLOAT)0.0833333*S33+(FLOAT)0.0416667*S34;\n" +" FLOAT4 m43 =\n" +" -(FLOAT)0.0833333*S41-(FLOAT)0.0416667*S42+(FLOAT)0.0833333*S43+(FLOAT)0.0416667*S44;\n" +" FLOAT4 m53 =\n" +" -(FLOAT)0.0833333*S51-(FLOAT)0.0416667*S52+(FLOAT)0.0833333*S53+(FLOAT)0.0416667*S54;\n" +" FLOAT4 m04 =\n" +" +(FLOAT)0.0833333*S01-(FLOAT)0.0416667*S02-(FLOAT)0.0833333*S03+(FLOAT)0.0416667*S04;\n" +" FLOAT4 m14 =\n" +" +(FLOAT)0.0833333*S11-(FLOAT)0.0416667*S12-(FLOAT)0.0833333*S13+(FLOAT)0.0416667*S14;\n" +" FLOAT4 m24 =\n" +" +(FLOAT)0.0833333*S21-(FLOAT)0.0416667*S22-(FLOAT)0.0833333*S23+(FLOAT)0.0416667*S24;\n" +" FLOAT4 m34 =\n" +" +(FLOAT)0.0833333*S31-(FLOAT)0.0416667*S32-(FLOAT)0.0833333*S33+(FLOAT)0.0416667*S34;\n" +" FLOAT4 m44 =\n" +" +(FLOAT)0.0833333*S41-(FLOAT)0.0416667*S42-(FLOAT)0.0833333*S43+(FLOAT)0.0416667*S44;\n" +" FLOAT4 m54 =\n" +" +(FLOAT)0.0833333*S51-(FLOAT)0.0416667*S52-(FLOAT)0.0833333*S53+(FLOAT)0.0416667*S54;\n" +" FLOAT4 m05=+(FLOAT)4.0*S01-(FLOAT)5.0*S03+S05;\n" +" FLOAT4 m15=+(FLOAT)4.0*S11-(FLOAT)5.0*S13+S15;\n" +" FLOAT4 m25=+(FLOAT)4.0*S21-(FLOAT)5.0*S23+S25;\n" +" FLOAT4 m35=+(FLOAT)4.0*S31-(FLOAT)5.0*S33+S35;\n" +" FLOAT4 m45=+(FLOAT)4.0*S41-(FLOAT)5.0*S43+S45;\n" +" FLOAT4 m55=+(FLOAT)4.0*S51-(FLOAT)5.0*S53+S55;\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*0),+m00-(FLOAT)1.25*m20+(FLOAT)0.25*m40);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*1),\n" +" +(FLOAT)0.666667*m10+(FLOAT)0.666667*m20-(FLOAT)0.166667*m30-(FLOAT)0.166667*m40);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*2),\n" +" -(FLOAT)0.666667*m10+(FLOAT)0.666667*m20+(FLOAT)0.166667*m30-(FLOAT)0.166667*m40);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*3),\n" +" -(FLOAT)0.0833333*m10-(FLOAT)0.0416667*m20+(FLOAT)0.0833333*m30+(FLOAT)0.0416667*m40);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*4),\n" +" +(FLOAT)0.0833333*m10-(FLOAT)0.0416667*m20-(FLOAT)0.0833333*m30+(FLOAT)0.0416667*m40);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*5),+(FLOAT)4.0*m10-(FLOAT)5.0*m30+m50);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*6),+m01-(FLOAT)1.25*m21+(FLOAT)0.25*m41);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*7),\n" +" +(FLOAT)0.666667*m11+(FLOAT)0.666667*m21-(FLOAT)0.166667*m31-(FLOAT)0.166667*m41);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*8),\n" +" -(FLOAT)0.666667*m11+(FLOAT)0.666667*m21+(FLOAT)0.166667*m31-(FLOAT)0.166667*m41);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*9),\n" +" -(FLOAT)0.0833333*m11-(FLOAT)0.0416667*m21+(FLOAT)0.0833333*m31+(FLOAT)0.0416667*m41);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*10),\n" +" +(FLOAT)0.0833333*m11-(FLOAT)0.0416667*m21-(FLOAT)0.0833333*m31+(FLOAT)0.0416667*m41);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*11),+(FLOAT)4.0*m11-(FLOAT)5.0*m31+m51);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*12),+m02-(FLOAT)1.25*m22+(FLOAT)0.25*m42);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*13),\n" +" +(FLOAT)0.666667*m12+(FLOAT)0.666667*m22-(FLOAT)0.166667*m32-(FLOAT)0.166667*m42);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*14),\n" +" -(FLOAT)0.666667*m12+(FLOAT)0.666667*m22+(FLOAT)0.166667*m32-(FLOAT)0.166667*m42);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*15),\n" +" -(FLOAT)0.0833333*m12-(FLOAT)0.0416667*m22+(FLOAT)0.0833333*m32+(FLOAT)0.0416667*m42);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*16),\n" +" +(FLOAT)0.0833333*m12-(FLOAT)0.0416667*m22-(FLOAT)0.0833333*m32+(FLOAT)0.0416667*m42);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*17),+(FLOAT)4.0*m12-(FLOAT)5.0*m32+m52);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*18),+m03-(FLOAT)1.25*m23+(FLOAT)0.25*m43);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*19),\n" +" +(FLOAT)0.666667*m13+(FLOAT)0.666667*m23-(FLOAT)0.166667*m33-(FLOAT)0.166667*m43);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*20),\n" +" -(FLOAT)0.666667*m13+(FLOAT)0.666667*m23+(FLOAT)0.166667*m33-(FLOAT)0.166667*m43);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*21),\n" +" -(FLOAT)0.0833333*m13-(FLOAT)0.0416667*m23+(FLOAT)0.0833333*m33+(FLOAT)0.0416667*m43);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*22),\n" +" +(FLOAT)0.0833333*m13-(FLOAT)0.0416667*m23-(FLOAT)0.0833333*m33+(FLOAT)0.0416667*m43);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*23),+(FLOAT)4.0*m13-(FLOAT)5.0*m33+m53);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*24),+m04-(FLOAT)1.25*m24+(FLOAT)0.25*m44);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*25),\n" +" +(FLOAT)0.666667*m14+(FLOAT)0.666667*m24-(FLOAT)0.166667*m34-(FLOAT)0.166667*m44);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*26),\n" +" -(FLOAT)0.666667*m14+(FLOAT)0.666667*m24+(FLOAT)0.166667*m34-(FLOAT)0.166667*m44);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*27),\n" +" -(FLOAT)0.0833333*m14-(FLOAT)0.0416667*m24+(FLOAT)0.0833333*m34+(FLOAT)0.0416667*m44);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*28),\n" +" +(FLOAT)0.0833333*m14-(FLOAT)0.0416667*m24-(FLOAT)0.0833333*m34+(FLOAT)0.0416667*m44);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*29),+(FLOAT)4.0*m14-(FLOAT)5.0*m34+m54);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*30),+m05-(FLOAT)1.25*m25+(FLOAT)0.25*m45);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*31),\n" +" +(FLOAT)0.666667*m15+(FLOAT)0.666667*m25-(FLOAT)0.166667*m35-(FLOAT)0.166667*m45);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*32),\n" +" -(FLOAT)0.666667*m15+(FLOAT)0.666667*m25+(FLOAT)0.166667*m35-(FLOAT)0.166667*m45);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*33),\n" +" -(FLOAT)0.0833333*m15-(FLOAT)0.0416667*m25+(FLOAT)0.0833333*m35+(FLOAT)0.0416667*m45);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*34),\n" +" +(FLOAT)0.0833333*m15-(FLOAT)0.0416667*m25-(FLOAT)0.0833333*m35+(FLOAT)0.0416667*m45);\n" +" WI_F(uOutput,(int2)(dstX,unitHeight_idx+unitHeight*35),+(FLOAT)4.0*m15-(FLOAT)5.0*m35+m55);\n" +" }\n" +" }\n" +"}\n" +; #ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "unary_buf", - { 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} - }, +const char* unary_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"inline float4 gelu(float4 in){\n" +" float4 value=0.79788458f*(0.044715f*in*in*in+in);\n" +" float4 x2=value*value;\n" +" float4 dst=value>(float4)5.0f ? (float4)1.0f : (value <= -(float4)5.0f ? -(float4)1.0f :\n" +" (value*(135135.0f+x2*(17325.0f+x2*(378.0f+x2))))/(135135.0f+x2*(62370.0f+x2*(3150.0f+x2*28.0f))));\n" +" return (1.0f+dst)*in*0.5f;\n" +"}\n" +"__kernel void unary_buf(GLOBAL_SIZE_3_DIMS\n" +" __global const INPUT_TYPE *input,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int height) {\n" +" const int channel_block_idx=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int hb=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(channel_block_idx,w,hb);\n" +" const int batch_idx=hb/height;\n" +" const int height_idx=hb % height;\n" +" const int offset=(((batch_idx*global_size_dim0+channel_block_idx)*height+height_idx)*global_size_dim1+w)*4;\n" +" float4 in=convert_float4(vload4(0,input+offset));\n" +" float4 out=OPERATOR;\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset);\n" +"}\n" +; #endif #ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "depthwise_conv2d_buf", - { 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} - }, +const char* depthwise_conv2d_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"#define DW_CONV_NEXT_LINE_CAL(x,y) "" x = mad(inValue0, weights0, x); "" x = mad(inValue1, weights1, x); "" x = mad(inValue2, weights2, x); "" y = mad(inValue1, weights0, y); "" y = mad(inValue2, weights1, y); "" y=mad(inValue3,weights2,y);\n" +"__kernel\n" +"void depthwise_conv2d_c4h1w4(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/4\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" COMPUTE_FLOAT4 outValue2=outValue0;\n" +" COMPUTE_FLOAT4 outValue3=outValue0;\n" +" const int out_w4_idx=out_w_idx << 2;\n" +" const int in_w_start_0=out_w4_idx*stride_hw.y-pad_hw.y;\n" +" const int in_w_start_1=in_w_start_0+stride_hw.y;\n" +" const int in_w_start_2=in_w_start_1+stride_hw.y;\n" +" const int in_w_start_3=in_w_start_2+stride_hw.y;\n" +" const int in_h_start=out_h_idx*stride_hw.x-pad_hw.x;\n" +" \n" +" for (int kh=0; kh= in_hw.x) continue;\n" +" \n" +" int inp_offset=(((b_idx*c_blocks+c_idx)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" for (int kw=0; kw= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+0,input+inp_offset));\n" +" COMPUTE_FLOAT4 inValue1=(in_w_start_1+kw_dilate<0 || in_w_start_1+kw_dilate >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+1*stride_hw.y,input+inp_offset));\n" +" COMPUTE_FLOAT4 inValue2=(in_w_start_2+kw_dilate<0 || in_w_start_2+kw_dilate >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+2*stride_hw.y,input+inp_offset));\n" +" COMPUTE_FLOAT4 inValue3=(in_w_start_3+kw_dilate<0 || in_w_start_3+kw_dilate >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+3*stride_hw.y,input+inp_offset));\n" +" //NC4HW4 [1,filterShape.x*filterShape.y,1,channelBlocks] x oc4\n" +" //index: [0,filterIdx,0,inChannelBlockIdx]\n" +" COMPUTE_FLOAT4 weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" outValue2=mad(inValue2,weights,outValue2);\n" +" outValue3=mad(inValue3,weights,outValue3);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +" outValue2=fmax(outValue2,(COMPUTE_FLOAT4)0);\n" +" outValue3=fmax(outValue3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue2=clamp(outValue2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue3=clamp(outValue3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w4_idx)*4;\n" +" const int remain=out_hw.y-out_w4_idx;\n" +" if (remain >= 4) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),2,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue3),3,output+out_offset);\n" +" } else if (remain == 3) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),2,output+out_offset);\n" +" } else if (remain == 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +" \n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_c4h1w2(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/4\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" const int out_w2_idx=out_w_idx << 1;\n" +" const int in_w_start_0=out_w2_idx*stride_hw.y-pad_hw.y;\n" +" const int in_w_start_1=in_w_start_0+stride_hw.y;\n" +" \n" +" const int in_h_start=out_h_idx*stride_hw.x-pad_hw.x;\n" +" \n" +" for (int kh=0; kh= in_hw.x) continue;\n" +" \n" +" int inp_offset=(((b_idx*c_blocks+c_idx)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" for (int kw=0; kw= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+0,input+inp_offset));\n" +" COMPUTE_FLOAT4 inValue1=(in_w_start_1+kw_dilate<0 || in_w_start_1+kw_dilate >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+1*stride_hw.y,input+inp_offset));\n" +" //NC4HW4 [1,filterShape.x*filterShape.y,1,channelBlocks] x oc4\n" +" //index: [0,filterIdx,0,inChannelBlockIdx]\n" +" COMPUTE_FLOAT4 weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w2_idx)*4;\n" +" const int remain=out_hw.y-out_w2_idx;\n" +" if (remain >= 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +" \n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_c4h1w1(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/4\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" const int in_w_start_0=out_w_idx*stride_hw.y-pad_hw.y;\n" +" const int in_h_start=out_h_idx*stride_hw.x-pad_hw.x;\n" +" \n" +" for (int kh=0; kh= in_hw.x) continue;\n" +" \n" +" int inp_offset=(((b_idx*c_blocks+c_idx)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" for (int kw=0; kw= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw_dilate+0,input+inp_offset));\n" +" //NC4HW4 [1,filterShape.x*filterShape.y,1,channelBlocks] x oc4\n" +" //index: [0,filterIdx,0,inChannelBlockIdx]\n" +" COMPUTE_FLOAT4 weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_s1_c8h1w4(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/4\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx+0,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" COMPUTE_FLOAT4 outValue2=outValue0;\n" +" COMPUTE_FLOAT4 outValue3=outValue0;\n" +" COMPUTE_FLOAT4 outValue4=CONVERT_COMPUTE_FLOAT4(vload4(c_idx+1,bias));\n" +" COMPUTE_FLOAT4 outValue5=outValue4;\n" +" COMPUTE_FLOAT4 outValue6=outValue4;\n" +" COMPUTE_FLOAT4 outValue7=outValue4;\n" +" const int out_w4_idx=out_w_idx << 2;\n" +" const int in_w_start_0=out_w4_idx-pad_hw.y;\n" +" const int in_w_start_1=in_w_start_0+1;\n" +" const int in_w_start_2=in_w_start_0+2;\n" +" const int in_w_start_3=in_w_start_0+3;\n" +" const int in_h_start=out_h_idx-pad_hw.x;\n" +" \n" +" for (int kh=0; kh= in_hw.x) continue;\n" +" \n" +" int inp_offset_c0=(((b_idx*c_blocks+c_idx+0)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" int inp_offset_c1=(((b_idx*c_blocks+c_idx+1)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" for (int kw=0; kw= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+0,input+inp_offset_c0));\n" +" COMPUTE_FLOAT4 inValue1=(in_w_start_1+kw<0 || in_w_start_1+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+1,input+inp_offset_c0));\n" +" COMPUTE_FLOAT4 inValue2=(in_w_start_2+kw<0 || in_w_start_2+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+2,input+inp_offset_c0));\n" +" COMPUTE_FLOAT4 inValue3=(in_w_start_3+kw<0 || in_w_start_3+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+3,input+inp_offset_c0));\n" +" COMPUTE_FLOAT4 inValue4=(in_w_start_0+kw<0 || in_w_start_0+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+0,input+inp_offset_c1));\n" +" COMPUTE_FLOAT4 inValue5=(in_w_start_1+kw<0 || in_w_start_1+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+1,input+inp_offset_c1));\n" +" COMPUTE_FLOAT4 inValue6=(in_w_start_2+kw<0 || in_w_start_2+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+2,input+inp_offset_c1));\n" +" COMPUTE_FLOAT4 inValue7=(in_w_start_3+kw<0 || in_w_start_3+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+3,input+inp_offset_c1));\n" +" \n" +" //NC4HW4 [1,filterShape.x*filterShape.y,1,channelBlocks] x oc4\n" +" //index: [0,filterIdx,0,inChannelBlockIdx]\n" +" COMPUTE_FLOAT4 weights_0=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx+0)*4));\n" +" COMPUTE_FLOAT4 weights_1=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx+1)*4));\n" +" outValue0=mad(inValue0,weights_0,outValue0);\n" +" outValue1=mad(inValue1,weights_0,outValue1);\n" +" outValue2=mad(inValue2,weights_0,outValue2);\n" +" outValue3=mad(inValue3,weights_0,outValue3);\n" +" \n" +" outValue4=mad(inValue4,weights_1,outValue4);\n" +" outValue5=mad(inValue5,weights_1,outValue5);\n" +" outValue6=mad(inValue6,weights_1,outValue6);\n" +" outValue7=mad(inValue7,weights_1,outValue7);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +" outValue2=fmax(outValue2,(COMPUTE_FLOAT4)0);\n" +" outValue3=fmax(outValue3,(COMPUTE_FLOAT4)0);\n" +" \n" +" outValue4=fmax(outValue4,(COMPUTE_FLOAT4)0);\n" +" outValue5=fmax(outValue5,(COMPUTE_FLOAT4)0);\n" +" outValue6=fmax(outValue6,(COMPUTE_FLOAT4)0);\n" +" outValue7=fmax(outValue7,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue2=clamp(outValue2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue3=clamp(outValue3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" \n" +" outValue4=clamp(outValue4,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue5=clamp(outValue5,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue6=clamp(outValue6,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue7=clamp(outValue7,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w4_idx)*4;\n" +" const int remain=out_hw.y-out_w4_idx;\n" +" if (remain >= 4) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),2,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue3),3,output+out_offset);\n" +" } else if (remain == 3) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),2,output+out_offset);\n" +" } else if (remain == 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +" \n" +" if(c_idx+1 >= c_blocks) return;\n" +" \n" +" out_offset += out_hw.x*out_hw.y*4;\n" +" if (remain >= 4) {\n" +" vstore4(CONVERT_FLOAT4(outValue4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue5),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue6),2,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue7),3,output+out_offset);\n" +" } else if (remain == 3) {\n" +" vstore4(CONVERT_FLOAT4(outValue4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue5),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue6),2,output+out_offset);\n" +" } else if (remain == 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue5),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue4),0,output+out_offset);\n" +" }\n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_s1_c8h1w2(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/4\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx+0,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" COMPUTE_FLOAT4 outValue4=CONVERT_COMPUTE_FLOAT4(vload4(c_idx+1,bias));\n" +" COMPUTE_FLOAT4 outValue5=outValue4;\n" +" const int out_w2_idx=out_w_idx << 1;\n" +" const int in_w_start_0=out_w2_idx-pad_hw.y;\n" +" const int in_w_start_1=in_w_start_0+1;\n" +" const int in_h_start=out_h_idx-pad_hw.x;\n" +" \n" +" for (int kh=0; kh= in_hw.x) continue;\n" +" \n" +" int inp_offset_c0=(((b_idx*c_blocks+c_idx+0)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" int inp_offset_c1=(((b_idx*c_blocks+c_idx+1)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" for (int kw=0; kw= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+0,input+inp_offset_c0));\n" +" COMPUTE_FLOAT4 inValue1=(in_w_start_1+kw<0 || in_w_start_1+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+1,input+inp_offset_c0));\n" +" COMPUTE_FLOAT4 inValue4=(in_w_start_0+kw<0 || in_w_start_0+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+0,input+inp_offset_c1));\n" +" COMPUTE_FLOAT4 inValue5=(in_w_start_1+kw<0 || in_w_start_1+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+1,input+inp_offset_c1));\n" +" //NC4HW4 [1,filterShape.x*filterShape.y,1,channelBlocks] x oc4\n" +" //index: [0,filterIdx,0,inChannelBlockIdx]\n" +" COMPUTE_FLOAT4 weights_0=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx+0)*4));\n" +" COMPUTE_FLOAT4 weights_1=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx+1)*4));\n" +" outValue0=mad(inValue0,weights_0,outValue0);\n" +" outValue1=mad(inValue1,weights_0,outValue1);\n" +" \n" +" outValue4=mad(inValue4,weights_1,outValue4);\n" +" outValue5=mad(inValue5,weights_1,outValue5);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +" \n" +" outValue4=fmax(outValue4,(COMPUTE_FLOAT4)0);\n" +" outValue5=fmax(outValue5,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" \n" +" outValue4=clamp(outValue4,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue5=clamp(outValue5,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w2_idx)*4;\n" +" const int remain=out_hw.y-out_w2_idx;\n" +" if (remain >= 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +" \n" +" if(c_idx+1 >= c_blocks) return;\n" +" \n" +" out_offset += out_hw.x*out_hw.y*4;\n" +" if (remain >= 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue5),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue4),0,output+out_offset);\n" +" }\n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_s1_c4h1w4(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/4\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" COMPUTE_FLOAT4 outValue2=outValue0;\n" +" COMPUTE_FLOAT4 outValue3=outValue0;\n" +" const int out_w4_idx=out_w_idx << 2;\n" +" const int in_w_start_0=out_w4_idx-pad_hw.y;\n" +" const int in_w_start_1=in_w_start_0+1;\n" +" const int in_w_start_2=in_w_start_0+2;\n" +" const int in_w_start_3=in_w_start_0+3;\n" +" const int in_h_start=out_h_idx-pad_hw.x;\n" +" \n" +" COMPUTE_FLOAT4 inValue0,inValue1,inValue2,inValue3;\n" +" for (int kh=0; kh= in_hw.x) continue;\n" +" \n" +" int inp_offset=(((b_idx*c_blocks+c_idx)*in_hw.x+in_h_cur)* in_hw.y+in_w_start_0)*4;\n" +" for (int kw=0; kw= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+0,input+inp_offset));\n" +" inValue1=(in_w_start_1+kw<0 || in_w_start_1+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+1,input+inp_offset));\n" +" inValue2=(in_w_start_2+kw<0 || in_w_start_2+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+2,input+inp_offset));\n" +" inValue3=(in_w_start_3+kw<0 || in_w_start_3+kw >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(kw+3,input+inp_offset));\n" +" //NC4HW4 [1,filterShape.x*filterShape.y,1,channelBlocks] x oc4\n" +" //index: [0,filterIdx,0,inChannelBlockIdx]\n" +" COMPUTE_FLOAT4 weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" outValue2=mad(inValue2,weights,outValue2);\n" +" outValue3=mad(inValue3,weights,outValue3);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +" outValue2=fmax(outValue2,(COMPUTE_FLOAT4)0);\n" +" outValue3=fmax(outValue3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue2=clamp(outValue2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue3=clamp(outValue3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w4_idx)*4;\n" +" const int remain=out_hw.y-out_w4_idx;\n" +" if (remain >= 4) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),2,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue3),3,output+out_offset);\n" +" } else if (remain == 3) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),2,output+out_offset);\n" +" } else if (remain == 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_k3s1p1_c4h1w2(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/2\n" +" const int out_b_h_idx=get_global_id(1);// b*h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_hw.x;\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" const int out_w2_idx=out_w_idx << 1;\n" +" const int in_w_start_0=out_w2_idx-pad_hw.y;\n" +" const int in_h_start=out_h_idx-pad_hw.x;\n" +" COMPUTE_FLOAT4 inValue0,inValue1,inValue2,inValue3;\n" +" //first line\n" +" const int inp_offset=(((b_idx*c_blocks+c_idx)*in_hw.x+in_h_start)* in_hw.y+in_w_start_0)*4;\n" +" inValue0=(in_h_start<0 || in_w_start_0<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset));\n" +" inValue1=(in_h_start<0 || in_w_start_0+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(1,input+inp_offset));\n" +" inValue2=(in_h_start<0 || in_w_start_0+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2,input+inp_offset));\n" +" inValue3=(in_h_start<0 || in_w_start_0+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(3,input+inp_offset));\n" +" int filter_idx=mad24(0,filter_hw.y,0);\n" +" COMPUTE_FLOAT4 weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" filter_idx=mad24(0,filter_hw.y,1);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue1,weights,outValue0);\n" +" outValue1=mad(inValue2,weights,outValue1);\n" +" \n" +" filter_idx=mad24(0,filter_hw.y,2);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue2,weights,outValue0);\n" +" outValue1=mad(inValue3,weights,outValue1);\n" +" //second line\n" +" inValue0=(in_h_start+1 >= in_hw.x || in_w_start_0<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+0,input+inp_offset));\n" +" inValue1=(in_h_start+1 >= in_hw.x || in_w_start_0+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+1,input+inp_offset));\n" +" inValue2=(in_h_start+1 >= in_hw.x || in_w_start_0+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+2,input+inp_offset));\n" +" inValue3=(in_h_start+1 >= in_hw.x || in_w_start_0+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+3,input+inp_offset));\n" +" \n" +" filter_idx=mad24(1,filter_hw.y,0);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" filter_idx=mad24(1,filter_hw.y,1);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue1,weights,outValue0);\n" +" outValue1=mad(inValue2,weights,outValue1);\n" +" \n" +" filter_idx=mad24(1,filter_hw.y,2);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue2,weights,outValue0);\n" +" outValue1=mad(inValue3,weights,outValue1);\n" +" \n" +" //third line\n" +" inValue0=(in_h_start+2 >= in_hw.x || in_w_start_0<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+0,input+inp_offset));\n" +" inValue1=(in_h_start+2 >= in_hw.x || in_w_start_0+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+1,input+inp_offset));\n" +" inValue2=(in_h_start+2 >= in_hw.x || in_w_start_0+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+2,input+inp_offset));\n" +" inValue3=(in_h_start+2 >= in_hw.x || in_w_start_0+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+3,input+inp_offset));\n" +" \n" +" filter_idx=mad24(2,filter_hw.y,0);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" filter_idx=mad24(2,filter_hw.y,1);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue1,weights,outValue0);\n" +" outValue1=mad(inValue2,weights,outValue1);\n" +" \n" +" filter_idx=mad24(2,filter_hw.y,2);\n" +" weights=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue2,weights,outValue0);\n" +" outValue1=mad(inValue3,weights,outValue1);\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w2_idx)*4;\n" +" const int remain=out_hw.y-out_w2_idx;\n" +" if (remain >= 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +"}\n" +"__kernel\n" +"void depthwise_conv2d_k3s1p1_c4h2w2(GLOBAL_SIZE_2_DIMS __global const FLOAT *input,\n" +" __global const FLOAT *filter,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int channel,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int c_blocks) {\n" +" const int out_c_w_idx=get_global_id(0);// oc/4*ow/2\n" +" const int out_b_h_idx=get_global_id(1);// b*h/2\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_h_blocks=(out_hw.x+1)/2;\n" +" const int c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int b_idx=out_b_h_idx/out_h_blocks;\n" +" const int out_h_idx=out_b_h_idx % out_h_blocks;\n" +" COMPUTE_FLOAT4 outValue0=CONVERT_COMPUTE_FLOAT4(vload4(c_idx,bias));\n" +" COMPUTE_FLOAT4 outValue1=outValue0;\n" +" COMPUTE_FLOAT4 outValue2=outValue0;\n" +" COMPUTE_FLOAT4 outValue3=outValue0;\n" +" const int out_w2_idx=out_w_idx << 1;\n" +" const int in_w_start=out_w2_idx-pad_hw.y;\n" +" const int out_h2_idx=out_h_idx << 1;\n" +" const int in_h_start=out_h2_idx-pad_hw.x;\n" +" COMPUTE_FLOAT4 inValue0,inValue1,inValue2,inValue3;\n" +" //first line\n" +" const int inp_offset=(((b_idx*c_blocks+c_idx)*in_hw.x+in_h_start)* in_hw.y+in_w_start)*4;\n" +" inValue0=(in_h_start<0 || in_w_start<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(0,input+inp_offset));\n" +" inValue1=(in_h_start<0 || in_w_start+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(1,input+inp_offset));\n" +" inValue2=(in_h_start<0 || in_w_start+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2,input+inp_offset));\n" +" inValue3=(in_h_start<0 || in_w_start+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(3,input+inp_offset));\n" +" int filter_idx=mad24(0,filter_hw.y,0);\n" +" COMPUTE_FLOAT4 weights0=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights0,outValue0);\n" +" outValue1=mad(inValue1,weights0,outValue1);\n" +" filter_idx=mad24(0,filter_hw.y,1);\n" +" COMPUTE_FLOAT4 weights1=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue1,weights1,outValue0);\n" +" outValue1=mad(inValue2,weights1,outValue1);\n" +" \n" +" \n" +" filter_idx=mad24(0,filter_hw.y,2);\n" +" COMPUTE_FLOAT4 weights2=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue2,weights2,outValue0);\n" +" outValue1=mad(inValue3,weights2,outValue1);\n" +" //second line\n" +" inValue0=(in_h_start+1 >= in_hw.x || in_w_start<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+0,input+inp_offset));\n" +" inValue1=(in_h_start+1 >= in_hw.x || in_w_start+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+1,input+inp_offset));\n" +" inValue2=(in_h_start+1 >= in_hw.x || in_w_start+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+2,input+inp_offset));\n" +" inValue3=(in_h_start+1 >= in_hw.x || in_w_start+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_hw.y+3,input+inp_offset));\n" +" \n" +" DW_CONV_NEXT_LINE_CAL(outValue2,outValue3)\n" +" \n" +" filter_idx=mad24(1,filter_hw.y,0);\n" +" weights0=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights0,outValue0);\n" +" outValue1=mad(inValue1,weights0,outValue1);\n" +" filter_idx=mad24(1,filter_hw.y,1);\n" +" weights1=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue1,weights1,outValue0);\n" +" outValue1=mad(inValue2,weights1,outValue1);\n" +" \n" +" filter_idx=mad24(1,filter_hw.y,2);\n" +" weights2=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue2,weights2,outValue0);\n" +" outValue1=mad(inValue3,weights2,outValue1);\n" +" \n" +" //third line\n" +" inValue0=(in_h_start+2 >= in_hw.x || in_w_start<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+0,input+inp_offset));\n" +" inValue1=(in_h_start+2 >= in_hw.x || in_w_start+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+1,input+inp_offset));\n" +" inValue2=(in_h_start+2 >= in_hw.x || in_w_start+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+2,input+inp_offset));\n" +" inValue3=(in_h_start+2 >= in_hw.x || in_w_start+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(2*in_hw.y+3,input+inp_offset));\n" +" \n" +" DW_CONV_NEXT_LINE_CAL(outValue2,outValue3)\n" +" \n" +" filter_idx=mad24(2,filter_hw.y,0);\n" +" weights0=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue0,weights0,outValue0);\n" +" outValue1=mad(inValue1,weights0,outValue1);\n" +" filter_idx=mad24(2,filter_hw.y,1);\n" +" weights1=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue1,weights1,outValue0);\n" +" outValue1=mad(inValue2,weights1,outValue1);\n" +" \n" +" filter_idx=mad24(2,filter_hw.y,2);\n" +" weights2=CONVERT_COMPUTE_FLOAT4(vload4(0,filter+(filter_idx*c_blocks+c_idx)*4));\n" +" outValue0=mad(inValue2,weights2,outValue0);\n" +" outValue1=mad(inValue3,weights2,outValue1);\n" +" \n" +" //forth line\n" +" inValue0=(in_h_start+3 >= in_hw.x || in_w_start<0 ) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(3*in_hw.y+0,input+inp_offset));\n" +" inValue1=(in_h_start+3 >= in_hw.x || in_w_start+1 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(3*in_hw.y+1,input+inp_offset));\n" +" inValue2=(in_h_start+3 >= in_hw.x || in_w_start+2 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(3*in_hw.y+2,input+inp_offset));\n" +" inValue3=(in_h_start+3 >= in_hw.x || in_w_start+3 >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(3*in_hw.y+3,input+inp_offset));\n" +" \n" +" DW_CONV_NEXT_LINE_CAL(outValue2,outValue3)\n" +" \n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(COMPUTE_FLOAT4)0);\n" +" outValue1=fmax(outValue1,(COMPUTE_FLOAT4)0);\n" +" outValue2=fmax(outValue2,(COMPUTE_FLOAT4)0);\n" +" outValue3=fmax(outValue3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue1=clamp(outValue1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue2=clamp(outValue2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" outValue3=clamp(outValue3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((b_idx*c_blocks+c_idx)*out_hw.x+out_h2_idx)*out_hw.y+out_w2_idx)*4;\n" +" const int remain_w=out_hw.y-out_w2_idx;\n" +" const int remain_h=out_hw.x-out_h2_idx;\n" +" if(remain_w >= 2 && remain_h >= 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),out_hw.y+0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue3),out_hw.y+1,output+out_offset);\n" +" } else if(remain_w == 1 && remain_h >= 2) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue2),out_hw.y+0,output+out_offset);\n" +" } else if(remain_w >= 2 && remain_h == 1) {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(outValue1),1,output+out_offset);\n" +" } else {\n" +" vstore4(CONVERT_FLOAT4(outValue0),0,output+out_offset);\n" +" }\n" +"}\n" +; #endif #ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "winogradTransform_buf", - { 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} - }, +const char* winogradTransform_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_DIM2 "" __private int global_size_dim0,__private int global_size_dim1,\n" +"#define UNIFORM_BOUNDRY_CHECK(index0, index1) "" if(index0 >= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +"// [dstChannel,srcChannel,3,3] -> [4x4,srcChannelPad,dstChannelpad] (N,Kpad,Npad)\n" +"__kernel void winoTransWeightBuf2_3_1(GLOBAL_SIZE_DIM2\n" +" __global const float* input,// 0\n" +" __global FLOAT* output,\n" +" __private const int srcChannel,// 3\n" +" __private const int dstChannel,\n" +" __private const int srcChannelPad,// 6\n" +" __private const int dstChannelPad\n" +") {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" \n" +" const int src_c=pos.x;\n" +" const int dst_c=pos.y;\n" +" \n" +" const int out_offset=(0*srcChannelPad+src_c)*dstChannelPad+dst_c;\n" +" const int out_offset_add=srcChannelPad*dstChannelPad;\n" +" if(src_c >= srcChannel || dst_c >= dstChannel) {\n" +" for(int i=0; i<16; i++) {\n" +" output[out_offset+i*out_offset_add]=(FLOAT)0;\n" +" }\n" +" return;\n" +" }\n" +" \n" +" const int in_offset=(dst_c*srcChannel+src_c)*9;\n" +" FLOAT8 in=CONVERT_FLOAT8(vload8(0,input+in_offset));\n" +" FLOAT in8=input[in_offset+8];\n" +" \n" +" FLOAT GB_00=in.s0;\n" +" FLOAT GB_01=in.s1;\n" +" FLOAT GB_02=in.s2;\n" +" FLOAT GB_10=in.s0+in.s3+in.s6;\n" +" FLOAT GB_11=in.s1+in.s4+in.s7;\n" +" FLOAT GB_12=in.s2+in.s5+in8;\n" +" FLOAT GB_20=in.s0-in.s3+in.s6;\n" +" FLOAT GB_21=in.s1-in.s4+in.s7;\n" +" FLOAT GB_22=in.s2-in.s5+in8;\n" +" FLOAT GB_30=in.s6;\n" +" FLOAT GB_31=in.s7;\n" +" FLOAT GB_32=in8;\n" +" \n" +" FLOAT GBGT_00=GB_00;\n" +" FLOAT GBGT_01=GB_00+GB_01+GB_02;\n" +" FLOAT GBGT_02=GB_00-GB_01+GB_02;\n" +" FLOAT GBGT_03=GB_02;\n" +" \n" +" FLOAT GBGT_10=GB_10;\n" +" FLOAT GBGT_11=GB_10+GB_11+GB_12;\n" +" FLOAT GBGT_12=GB_10-GB_11+GB_12;\n" +" FLOAT GBGT_13=GB_12;\n" +" \n" +" FLOAT GBGT_20=GB_20;\n" +" FLOAT GBGT_21=GB_20+GB_21+GB_22;\n" +" FLOAT GBGT_22=GB_20-GB_21+GB_22;\n" +" FLOAT GBGT_23=GB_22;\n" +" \n" +" FLOAT GBGT_30=GB_30;\n" +" FLOAT GBGT_31=GB_30+GB_31+GB_32;\n" +" FLOAT GBGT_32=GB_30-GB_31+GB_32;\n" +" FLOAT GBGT_33=GB_32;\n" +" output[out_offset+0*out_offset_add]=GBGT_00;\n" +" output[out_offset+1*out_offset_add]=GBGT_01;\n" +" output[out_offset+2*out_offset_add]=GBGT_02;\n" +" output[out_offset+3*out_offset_add]=GBGT_03;\n" +" output[out_offset+4*out_offset_add]=GBGT_10;\n" +" output[out_offset+5*out_offset_add]=GBGT_11;\n" +" output[out_offset+6*out_offset_add]=GBGT_12;\n" +" output[out_offset+7*out_offset_add]=GBGT_13;\n" +" output[out_offset+8*out_offset_add]=GBGT_20;\n" +" output[out_offset+9*out_offset_add]=GBGT_21;\n" +" output[out_offset+10*out_offset_add]=GBGT_22;\n" +" output[out_offset+11*out_offset_add]=GBGT_23;\n" +" output[out_offset+12*out_offset_add]=GBGT_30;\n" +" output[out_offset+13*out_offset_add]=GBGT_31;\n" +" output[out_offset+14*out_offset_add]=GBGT_32;\n" +" output[out_offset+15*out_offset_add]=GBGT_33;\n" +"}\n" +"__kernel void winoTransSrcBuf2_3_1(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* uInput,// 0\n" +" __global FLOAT* uOutput,__private const int unitWidth,\n" +" __private const int unitHeight,// 3\n" +" __private const int padX,__private const int padY,\n" +" __private const int srcWidth,// 6\n" +" __private const int srcHeight,__private const int srcChannelC4,\n" +" __private const int dstHeightPad,__private const int srcChannelPad,\n" +" __private const int batchOffset) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1)); \n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" \n" +" if(pos.x >= unitWidth*unitHeight || pos.y >= srcChannelC4) {\n" +" return;\n" +" }\n" +" int unitWidth_idx=pos.x % unitWidth;\n" +" int unitHeight_idx=pos.x/unitWidth;\n" +" int2 realPos=(int2)(unitWidth_idx,unitHeight_idx);\n" +" int dstXOrigin=pos.y;\n" +" int batchIndex=pos.y/srcChannelC4;\n" +" int srcZ=pos.y % srcChannelC4;\n" +" int dstYOrigin=unitWidth*unitHeight_idx+unitWidth_idx;\n" +" int dstHeight=(unitWidth*unitHeight+3)/4;\n" +" int dstY=dstYOrigin/4;\n" +" int dstX=dstYOrigin % 4+4*dstXOrigin;\n" +" batchIndex=batchOffset;\n" +" {\n" +" int sxStart=(realPos.x)*2-padX;\n" +" int syStart=(realPos.y)*2-padY;\n" +" FLOAT4 S00;\n" +" FLOAT4 S10;\n" +" FLOAT4 S20;\n" +" FLOAT4 S30;\n" +" FLOAT4 S01;\n" +" FLOAT4 S11;\n" +" FLOAT4 S21;\n" +" FLOAT4 S31;\n" +" FLOAT4 S02;\n" +" FLOAT4 S12;\n" +" FLOAT4 S22;\n" +" FLOAT4 S32;\n" +" FLOAT4 S03;\n" +" FLOAT4 S13;\n" +" FLOAT4 S23;\n" +" FLOAT4 S33;\n" +" \n" +" int inp_offset=(((batchIndex*srcChannelC4+srcZ)*srcHeight+syStart)*srcWidth+sxStart)*4;\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=0+syStart;\n" +" \n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S00=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=0+syStart;\n" +" \n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S10=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=0+syStart;\n" +" \n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S20=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=0+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S30=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12);\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S01=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S11=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S21=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S31=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth+12);\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S02=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S12=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S22=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S32=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth+12);\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S03=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S13=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S23=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S33=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth+12);\n" +" }\n" +" FLOAT4 m00=+S00-S02;\n" +" FLOAT4 m10=+S10-S12;\n" +" FLOAT4 m20=+S20-S22;\n" +" FLOAT4 m30=+S30-S32;\n" +" FLOAT4 m01=+(FLOAT)0.5f*S01+(FLOAT)0.5f*S02;\n" +" FLOAT4 m11=+(FLOAT)0.5f*S11+(FLOAT)0.5f*S12;\n" +" FLOAT4 m21=+(FLOAT)0.5f*S21+(FLOAT)0.5f*S22;\n" +" FLOAT4 m31=+(FLOAT)0.5f*S31+(FLOAT)0.5f*S32;\n" +" FLOAT4 m02=-(FLOAT)0.5f*S01+(FLOAT)0.5f*S02;\n" +" FLOAT4 m12=-(FLOAT)0.5f*S11+(FLOAT)0.5f*S12;\n" +" FLOAT4 m22=-(FLOAT)0.5f*S21+(FLOAT)0.5f*S22;\n" +" FLOAT4 m32=-(FLOAT)0.5f*S31+(FLOAT)0.5f*S32;\n" +" FLOAT4 m03=-S01+S03;\n" +" FLOAT4 m13=-S11+S13;\n" +" FLOAT4 m23=-S21+S23;\n" +" FLOAT4 m33=-S31+S33;\n" +" \n" +" //NC4HW4 [alpha*alpha,srcChannelPad,dstHeightPad]\n" +" //index: [0,dstXOrigin,dstY,dstYOrigin % 4]\n" +" int out_offset=(0*srcChannelPad+4*dstXOrigin)*dstHeightPad+dstYOrigin;\n" +" int batch_offset=srcChannelPad*dstHeightPad;\n" +" \n" +" FLOAT4 res=(+m00-m20);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" out_offset += batch_offset;\n" +" res=(+(FLOAT)0.5f*m10+(FLOAT)0.5f*m20);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-(FLOAT)0.5f*m10+(FLOAT)0.5f*m20);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-m10+m30);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" \n" +" out_offset += batch_offset;\n" +" res=(+m01-m21);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(+(FLOAT)0.5f*m11+(FLOAT)0.5f*m21);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-(FLOAT)0.5f*m11+(FLOAT)0.5f*m21);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-m11+m31);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(+m02-m22);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(+(FLOAT)0.5f*m12+(FLOAT)0.5f*m22);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-(FLOAT)0.5f*m12+(FLOAT)0.5f*m22);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-m12+m32);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(+m03-m23);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(+(FLOAT)0.5f*m13+(FLOAT)0.5f*m23);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-(FLOAT)0.5f*m13+(FLOAT)0.5f*m23);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" \n" +" out_offset += batch_offset;\n" +" res=(-m13+m33);\n" +" uOutput[out_offset]=res.x;\n" +" uOutput[out_offset+dstHeightPad]=res.y;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad]=res.z;\n" +" uOutput[out_offset+dstHeightPad+dstHeightPad+dstHeightPad]=res.w;\n" +" }\n" +"}\n" +"__kernel void winoTransDstBuf2_3_1(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* uInput,\n" +" __global const FLOAT* uBias,\n" +" __global FLOAT* uOutput,\n" +" __private const int unitWidth,//wUnit\n" +" __private const int unitHeight,//hUnit\n" +" __private const int dstWidth,\n" +" __private const int dstHeight,\n" +" __private const int dstChannelC4,\n" +" __private const int srcWidthPad,\n" +" __private const int dstChannelPad,\n" +" __private const int batchOffset) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" int unitWidth_idx=pos.x % unitWidth;\n" +" int unitHeight_idx=pos.x/unitWidth;\n" +" int2 realPos=(int2)(unitWidth_idx,unitHeight_idx);\n" +" int srcWidth=(unitWidth*unitHeight+3)/4;\n" +" int dstXOrigin=unitWidth*unitHeight_idx+unitWidth_idx;\n" +" int dstX=dstXOrigin/4;\n" +" int dstY=4*pos.y+dstXOrigin % 4;\n" +" int oz=pos.y % dstChannelC4;\n" +" \n" +" FLOAT4 bias=vload4(0,uBias+oz*4);\n" +" int batchIndex=pos.y/dstChannelC4;\n" +" batchIndex=batchOffset;\n" +" {\n" +" int oyStart=realPos.y*2;\n" +" int oxStart=realPos.x*2;\n" +" \n" +" // [alpha2,srcWidthPad,dstChannelPad]\n" +" //index: [0,dstXOrigin,4*oz]\n" +" const int inp_offset=(0*srcWidthPad+dstXOrigin)*dstChannelPad+4*oz;\n" +" const int b_offset=dstChannelPad*srcWidthPad;\n" +" FLOAT4 S00=vload4(0,uInput+inp_offset+b_offset*0);\n" +" FLOAT4 S10=vload4(0,uInput+inp_offset+b_offset*1);\n" +" FLOAT4 S20=vload4(0,uInput+inp_offset+b_offset*2);\n" +" FLOAT4 S30=vload4(0,uInput+inp_offset+b_offset*3);\n" +" FLOAT4 S01=vload4(0,uInput+inp_offset+b_offset*4);\n" +" FLOAT4 S11=vload4(0,uInput+inp_offset+b_offset*5);\n" +" FLOAT4 S21=vload4(0,uInput+inp_offset+b_offset*6);\n" +" FLOAT4 S31=vload4(0,uInput+inp_offset+b_offset*7);\n" +" FLOAT4 S02=vload4(0,uInput+inp_offset+b_offset*8);\n" +" FLOAT4 S12=vload4(0,uInput+inp_offset+b_offset*9);\n" +" FLOAT4 S22=vload4(0,uInput+inp_offset+b_offset*10);\n" +" FLOAT4 S32=vload4(0,uInput+inp_offset+b_offset*11);\n" +" FLOAT4 S03=vload4(0,uInput+inp_offset+b_offset*12);\n" +" FLOAT4 S13=vload4(0,uInput+inp_offset+b_offset*13);\n" +" FLOAT4 S23=vload4(0,uInput+inp_offset+b_offset*14);\n" +" FLOAT4 S33=vload4(0,uInput+inp_offset+b_offset*15);\n" +" FLOAT4 m00=+S00+S01+S02;\n" +" FLOAT4 m10=+S10+S11+S12;\n" +" FLOAT4 m20=+S20+S21+S22;\n" +" FLOAT4 m30=+S30+S31+S32;\n" +" FLOAT4 m01=+S01-S02+S03;\n" +" FLOAT4 m11=+S11-S12+S13;\n" +" FLOAT4 m21=+S21-S22+S23;\n" +" FLOAT4 m31=+S31-S32+S33;\n" +" \n" +" //NC4HW4 [batch,dstChannelC4,dstHeight,dstWidth]\n" +" //index: [batchIndex,oz,oyStart,oxStart]\n" +" int out_offset=(((batchIndex*dstChannelC4+ oz)*dstHeight+oyStart)*dstWidth+oxStart)*4;\n" +" {\n" +" int ox=oxStart+0;\n" +" int oy=oyStart+0;\n" +" if (ox= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +" \n" +"#pragma OPENCL EXTENSION cl_intel_subgroups : enable\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void winoTransSrcBuf2_3_1_c16_c16(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* uInput,// 0\n" +" __global FLOAT* uOutput,__private const int unitWidth,\n" +" __private const int unitHeight,// 3\n" +" __private const int padX,__private const int padY,\n" +" __private const int srcWidth,// 6\n" +" __private const int srcHeight,__private const int srcChannelC4,__private const int srcChannelC16,__private const int dstHeight,\n" +" __private const int batchOffset,\n" +" __private const int input_pad_left,__private const int input_pad_right) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1)); \n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" const int unitWidth_idx=pos.x % unitWidth;\n" +" const int unitHeight_idx=pos.x/unitWidth;\n" +" const int sglid=get_sub_group_local_id();\n" +" const int pos_y=get_group_id(1);\n" +" int2 realPos=(int2)(unitWidth_idx,unitHeight_idx);\n" +" int src_pitch=srcWidth+input_pad_left+input_pad_right;\n" +" \n" +" {\n" +" int sxStart=(realPos.x)*2-padX;\n" +" int syStart=(realPos.y)*2-padY;\n" +" FLOAT4 S[4];\n" +" \n" +" int inp_offset=(((batchOffset*srcChannelC16+pos_y)*srcHeight+syStart)*src_pitch+sxStart+input_pad_left)*16;\n" +" for(int i=0; i<4; ++i){\n" +" int sy=i+syStart;\n" +" if(sy<0 || sy >= srcHeight){\n" +" S[i]=(FLOAT4)0;\n" +" }else{\n" +"#ifdef MNN_SUPPORT_FP16\n" +" S[i]=as_half4(intel_sub_group_block_read_us4((__global ushort*)(uInput+inp_offset)));\n" +"#else\n" +" S[i]=as_float4(intel_sub_group_block_read4((__global uint*)(uInput+inp_offset)));\n" +"#endif\n" +" }\n" +" inp_offset += 16*src_pitch;\n" +" }\n" +" FLOAT m00=+S[0].s0-S[2].s0;\n" +" FLOAT m10=+S[0].s1-S[2].s1;\n" +" FLOAT m20=+S[0].s2-S[2].s2;\n" +" FLOAT m30=+S[0].s3-S[2].s3;\n" +" FLOAT m01=+(FLOAT)0.5f*S[1].s0+(FLOAT)0.5f*S[2].s0;\n" +" FLOAT m11=+(FLOAT)0.5f*S[1].s1+(FLOAT)0.5f*S[2].s1;\n" +" FLOAT m21=+(FLOAT)0.5f*S[1].s2+(FLOAT)0.5f*S[2].s2;\n" +" FLOAT m31=+(FLOAT)0.5f*S[1].s3+(FLOAT)0.5f*S[2].s3;\n" +" FLOAT m02=-(FLOAT)0.5f*S[1].s0+(FLOAT)0.5f*S[2].s0;\n" +" FLOAT m12=-(FLOAT)0.5f*S[1].s1+(FLOAT)0.5f*S[2].s1;\n" +" FLOAT m22=-(FLOAT)0.5f*S[1].s2+(FLOAT)0.5f*S[2].s2;\n" +" FLOAT m32=-(FLOAT)0.5f*S[1].s3+(FLOAT)0.5f*S[2].s3;\n" +" FLOAT m03=-S[1].s0+S[3].s0;\n" +" FLOAT m13=-S[1].s1+S[3].s1;\n" +" FLOAT m23=-S[1].s2+S[3].s2;\n" +" FLOAT m33=-S[1].s3+S[3].s3;\n" +" \n" +" //NC4HW4 [alpha*alpha,srcChannelC16,dstHeight,16]\n" +" //index: [0,pos.y/16,pos.x,0]\n" +" int out_offset=(pos_y*dstHeight+pos.x)*16+sglid;\n" +" int batch_offset=srcChannelC16*dstHeight*16;\n" +" uOutput[out_offset+0*batch_offset]=+m00-m20;\n" +" uOutput[out_offset+1*batch_offset]=+(FLOAT)0.5f*m10+(FLOAT)0.5f*m20;\n" +" uOutput[out_offset+2*batch_offset]=-(FLOAT)0.5f*m10+(FLOAT)0.5f*m20;\n" +" uOutput[out_offset+3*batch_offset]=-m10+m30;\n" +" uOutput[out_offset+4*batch_offset]=+m01-m21;\n" +" uOutput[out_offset+5*batch_offset]=+(FLOAT)0.5f*m11+(FLOAT)0.5f*m21;\n" +" uOutput[out_offset+6*batch_offset]=-(FLOAT)0.5f*m11+(FLOAT)0.5f*m21;\n" +" uOutput[out_offset+7*batch_offset]=-m11+m31;\n" +" uOutput[out_offset+8*batch_offset]=+m02-m22;\n" +" uOutput[out_offset+9*batch_offset]=+(FLOAT)0.5f*m12+(FLOAT)0.5f*m22;\n" +" uOutput[out_offset+10*batch_offset]=-(FLOAT)0.5f*m12+(FLOAT)0.5f*m22;\n" +" uOutput[out_offset+11*batch_offset]=-m12+m32;\n" +" uOutput[out_offset+12*batch_offset]=+m03-m23;\n" +" uOutput[out_offset+13*batch_offset]=+(FLOAT)0.5f*m13+(FLOAT)0.5f*m23;\n" +" uOutput[out_offset+14*batch_offset]=-(FLOAT)0.5f*m13+(FLOAT)0.5f*m23;\n" +" uOutput[out_offset+15*batch_offset]=-m13+m33;\n" +" }\n" +"}\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void winoTransDstBuf2_3_1_c16_c16(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* uInput,\n" +" __global const FLOAT* uBias,\n" +" __global FLOAT* uOutput,\n" +" __private const int unitWidth,//wUnit\n" +" __private const int unitHeight,//hUnit\n" +" __private const int dstWidth,\n" +" __private const int dstHeight,\n" +" __private const int dstChannelC4,__private const int dstChannelC16,__private const int srcWidth,\n" +" __private const int batchOffset,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" const int unitWidth_idx=pos.x % unitWidth;\n" +" const int unitHeight_idx=pos.x/unitWidth; \n" +" const int sglid=get_sub_group_local_id();\n" +" const int pos_y=get_group_id(1);\n" +" int2 realPos=(int2)(unitWidth_idx,unitHeight_idx);\n" +" \n" +" FLOAT bias=uBias[pos.y];\n" +" {\n" +" int oyStart=realPos.y*2;\n" +" int oxStart=realPos.x*2;\n" +" \n" +" //NC4HW4 [alpha2,dstChannelC16,wUnit*hUnit,16]\n" +" //index: [0,pos.y/4,pos.x,pos.y%4]\n" +" const int inp_offset=(pos_y*srcWidth+pos.x)*16+sglid;\n" +" const int ic_offset=16*srcWidth*dstChannelC16;\n" +" FLOAT S00=uInput[inp_offset+ic_offset*0];\n" +" FLOAT S10=uInput[inp_offset+ic_offset*1];\n" +" FLOAT S20=uInput[inp_offset+ic_offset*2];\n" +" FLOAT S30=uInput[inp_offset+ic_offset*3];\n" +" FLOAT S01=uInput[inp_offset+ic_offset*4];\n" +" FLOAT S11=uInput[inp_offset+ic_offset*5];\n" +" FLOAT S21=uInput[inp_offset+ic_offset*6];\n" +" FLOAT S31=uInput[inp_offset+ic_offset*7];\n" +" FLOAT S02=uInput[inp_offset+ic_offset*8];\n" +" FLOAT S12=uInput[inp_offset+ic_offset*9];\n" +" FLOAT S22=uInput[inp_offset+ic_offset*10];\n" +" FLOAT S32=uInput[inp_offset+ic_offset*11];\n" +" FLOAT S03=uInput[inp_offset+ic_offset*12];\n" +" FLOAT S13=uInput[inp_offset+ic_offset*13];\n" +" FLOAT S23=uInput[inp_offset+ic_offset*14];\n" +" FLOAT S33=uInput[inp_offset+ic_offset*15];\n" +" FLOAT m00=+S00+S01+S02;\n" +" FLOAT m10=+S10+S11+S12;\n" +" FLOAT m20=+S20+S21+S22;\n" +" FLOAT m30=+S30+S31+S32;\n" +" FLOAT m01=+S01-S02+S03;\n" +" FLOAT m11=+S11-S12+S13;\n" +" FLOAT m21=+S21-S22+S23;\n" +" FLOAT m31=+S31-S32+S33;\n" +" \n" +" //NC4HW4 [batch,dstChannelC4,dstHeight,dstWidth]\n" +" //index: [batchOffset,pos.y,oyStart,oxStart]\n" +" int dst_pitch=dstWidth+output_pad_left+output_pad_right;\n" +" int out_offset=(((batchOffset*dstChannelC16+ pos_y)*dstHeight+oyStart)*dst_pitch+oxStart+output_pad_left)*16+sglid;\n" +" {\n" +" FLOAT2 res=(FLOAT2)(bias+m00+m10+m20,bias+m10-m20+m30);\n" +"#ifdef RELU\n" +" res=max(res,(FLOAT2)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" res=clamp(res,(FLOAT2)0,(FLOAT2)6);\n" +"#endif\n" +"#if OUTPUT_LEFTOVERS\n" +" uOutput[out_offset]=res.x;\n" +" if(oxStart+1< dstWidth){\n" +" uOutput[out_offset+16]=res.y;\n" +" }\n" +"#else\n" +"#ifdef MNN_SUPPORT_FP16\n" +" intel_sub_group_block_write_us2((__global ushort*)(uOutput+out_offset),as_ushort2(res));\n" +"#else\n" +" intel_sub_group_block_write2((__global uint*)(uOutput+out_offset),as_uint2(res));\n" +"#endif\n" +"#endif //OUTPUT_LEFTOVERS\n" +" }\n" +" {\n" +" int oy=oyStart+1;\n" +" if (oy= srcWidth || sy<0 || sy >= srcHeight);\n" +" S00=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=0+syStart;\n" +" \n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S10=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=0+syStart;\n" +" \n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S20=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=0+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S30=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12);\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S01=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S11=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S21=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=1+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S31=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+4*srcWidth+12);\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S02=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S12=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S22=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=2+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S32=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+8*srcWidth+12);\n" +" }\n" +" {\n" +" int sx=0+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S03=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth);\n" +" }\n" +" {\n" +" int sx=1+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S13=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth+4);\n" +" }\n" +" {\n" +" int sx=2+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S23=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth+8);\n" +" }\n" +" {\n" +" int sx=3+sxStart;\n" +" int sy=3+syStart;\n" +" bool outBound=(sx<0 || sx >= srcWidth || sy<0 || sy >= srcHeight);\n" +" S33=outBound ? (FLOAT4)(0) : vload4(0,uInput+inp_offset+12*srcWidth+12);\n" +" }\n" +" FLOAT4 m00=+S00-S02;\n" +" FLOAT4 m10=+S10-S12;\n" +" FLOAT4 m20=+S20-S22;\n" +" FLOAT4 m30=+S30-S32;\n" +" FLOAT4 m01=+(FLOAT)0.5f*S01+(FLOAT)0.5f*S02;\n" +" FLOAT4 m11=+(FLOAT)0.5f*S11+(FLOAT)0.5f*S12;\n" +" FLOAT4 m21=+(FLOAT)0.5f*S21+(FLOAT)0.5f*S22;\n" +" FLOAT4 m31=+(FLOAT)0.5f*S31+(FLOAT)0.5f*S32;\n" +" FLOAT4 m02=-(FLOAT)0.5f*S01+(FLOAT)0.5f*S02;\n" +" FLOAT4 m12=-(FLOAT)0.5f*S11+(FLOAT)0.5f*S12;\n" +" FLOAT4 m22=-(FLOAT)0.5f*S21+(FLOAT)0.5f*S22;\n" +" FLOAT4 m32=-(FLOAT)0.5f*S31+(FLOAT)0.5f*S32;\n" +" FLOAT4 m03=-S01+S03;\n" +" FLOAT4 m13=-S11+S13;\n" +" FLOAT4 m23=-S21+S23;\n" +" FLOAT4 m33=-S31+S33;\n" +" \n" +" //NC4HW4 [alpha*alpha,srcChannelC16,dstHeight,16]\n" +" //index: [0,pos.y/4,pos.x,pos.y % 4]\n" +" int out_offset=((pos.y/4)*dstHeight+pos.x)*16+(pos.y % 4)*4;\n" +" int batch_offset=srcChannelC16*dstHeight*16;\n" +" vstore4(+m00-m20,0,uOutput+out_offset+0*batch_offset);\n" +" vstore4(+(FLOAT)0.5f*m10+(FLOAT)0.5f*m20,0,uOutput+out_offset+1*batch_offset);\n" +" vstore4(-(FLOAT)0.5f*m10+(FLOAT)0.5f*m20,0,uOutput+out_offset+2*batch_offset);\n" +" vstore4(-m10+m30,0,uOutput+out_offset+3*batch_offset);\n" +" vstore4(+m01-m21,0,uOutput+out_offset+4*batch_offset);\n" +" vstore4(+(FLOAT)0.5f*m11+(FLOAT)0.5f*m21,0,uOutput+out_offset+5*batch_offset);\n" +" vstore4(-(FLOAT)0.5f*m11+(FLOAT)0.5f*m21,0,uOutput+out_offset+6*batch_offset);\n" +" vstore4(-m11+m31,0,uOutput+out_offset+7*batch_offset);\n" +" vstore4(+m02-m22,0,uOutput+out_offset+8*batch_offset);\n" +" vstore4(+(FLOAT)0.5f*m12+(FLOAT)0.5f*m22,0,uOutput+out_offset+9*batch_offset);\n" +" vstore4(-(FLOAT)0.5f*m12+(FLOAT)0.5f*m22,0,uOutput+out_offset+10*batch_offset);\n" +" vstore4(-m12+m32,0,uOutput+out_offset+11*batch_offset);\n" +" vstore4(+m03-m23,0,uOutput+out_offset+12*batch_offset);\n" +" vstore4(+(FLOAT)0.5f*m13+(FLOAT)0.5f*m23,0,uOutput+out_offset+13*batch_offset);\n" +" vstore4(-(FLOAT)0.5f*m13+(FLOAT)0.5f*m23,0,uOutput+out_offset+14*batch_offset);\n" +" vstore4(-m13+m33,0,uOutput+out_offset+15*batch_offset);\n" +" }\n" +"}\n" +"__kernel void winoTransDstBuf2_3_1_c16_c4(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* uInput,\n" +" __global const FLOAT* uBias,\n" +" __global FLOAT* uOutput,\n" +" __private const int unitWidth,//wUnit\n" +" __private const int unitHeight,//hUnit\n" +" __private const int dstWidth,\n" +" __private const int dstHeight,\n" +" __private const int dstChannelC4,__private const int dstChannelC16,__private const int srcWidth,\n" +" __private const int batchOffset,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" int unitWidth_idx=pos.x % unitWidth;\n" +" int unitHeight_idx=pos.x/unitWidth;\n" +" int2 realPos=(int2)(unitWidth_idx,unitHeight_idx);\n" +" \n" +" FLOAT4 bias=vload4(0,uBias+pos.y*4);\n" +" {\n" +" int oyStart=realPos.y*2;\n" +" int oxStart=realPos.x*2;\n" +" \n" +" //NC4HW4 [alpha2,dstChannelC16,wUnit*hUnit,16]\n" +" //index: [0,pos.y/4,pos.x,pos.y%4]\n" +" const int inp_offset=((pos.y/4)*srcWidth+pos.x)*16+(pos.y % 4)*4;\n" +" const int ic_offset=16*srcWidth*dstChannelC16;\n" +" FLOAT4 S00=vload4(0,uInput+inp_offset+ic_offset*0);\n" +" FLOAT4 S10=vload4(0,uInput+inp_offset+ic_offset*1);\n" +" FLOAT4 S20=vload4(0,uInput+inp_offset+ic_offset*2);\n" +" FLOAT4 S30=vload4(0,uInput+inp_offset+ic_offset*3);\n" +" FLOAT4 S01=vload4(0,uInput+inp_offset+ic_offset*4);\n" +" FLOAT4 S11=vload4(0,uInput+inp_offset+ic_offset*5);\n" +" FLOAT4 S21=vload4(0,uInput+inp_offset+ic_offset*6);\n" +" FLOAT4 S31=vload4(0,uInput+inp_offset+ic_offset*7);\n" +" FLOAT4 S02=vload4(0,uInput+inp_offset+ic_offset*8);\n" +" FLOAT4 S12=vload4(0,uInput+inp_offset+ic_offset*9);\n" +" FLOAT4 S22=vload4(0,uInput+inp_offset+ic_offset*10);\n" +" FLOAT4 S32=vload4(0,uInput+inp_offset+ic_offset*11);\n" +" FLOAT4 S03=vload4(0,uInput+inp_offset+ic_offset*12);\n" +" FLOAT4 S13=vload4(0,uInput+inp_offset+ic_offset*13);\n" +" FLOAT4 S23=vload4(0,uInput+inp_offset+ic_offset*14);\n" +" FLOAT4 S33=vload4(0,uInput+inp_offset+ic_offset*15);\n" +" FLOAT4 m00=+S00+S01+S02;\n" +" FLOAT4 m10=+S10+S11+S12;\n" +" FLOAT4 m20=+S20+S21+S22;\n" +" FLOAT4 m30=+S30+S31+S32;\n" +" FLOAT4 m01=+S01-S02+S03;\n" +" FLOAT4 m11=+S11-S12+S13;\n" +" FLOAT4 m21=+S21-S22+S23;\n" +" FLOAT4 m31=+S31-S32+S33;\n" +" \n" +" //NC4HW4 [batch,dstChannelC4,dstHeight,dstWidth]\n" +" //index: [batchOffset,pos.y,oyStart,oxStart]\n" +" int out_offset=(((batchOffset*dstChannelC4+ pos.y)*dstHeight+oyStart)*dstWidth+oxStart)*4;\n" +" {\n" +" int ox=oxStart+0;\n" +" int oy=oyStart+0;\n" +" if (ox> 2;\n" +" const int area_4=(shape.z+3) >> 2;\n" +" const int in_offset=((b*channel_4+c_4)*area_4*2+hw_4)*16;\n" +" const int out_offset=((b*channel_4+c_4)*area_4+hw_4)*16;\n" +" float16 valueL=convert_float16(vload16(0,input+in_offset));\n" +" float16 valueR=convert_float16(vload16(area_4,input+in_offset));\n" +" #ifdef DOUBLE_INPUTS\n" +" float4 valueConstL=convert_float4(vload4(hw,input1));\n" +" float4 valueConstR=convert_float4(vload4(area_4+hw,input1));\n" +" valueL += (float16)((float4)valueConstL.x,(float4)valueConstL.y,(float4)valueConstL.z,(float4)valueConstL.w);\n" +" valueR += (float16)((float4)valueConstR.x,(float4)valueConstR.y,(float4)valueConstR.z,(float4)valueConstR.w);\n" +" #endif\n" +" float16 out=(erf(valueR*(float16)0.7071067932881648)+(float16)1.0)*valueR*(float16)0.5;\n" +" out *= valueL;\n" +" vstore16(CONVERT_FLOAT16(out),0,output+out_offset);\n" +"#else\n" +" const int hw=pos.z;\n" +" \n" +" const int channel_4=(shape.y+3) >> 2;\n" +" const int in_offset=((b*channel_4+c_4)*shape.z*2+hw)*4;\n" +" const int out_offset=((b*channel_4+c_4)*shape.z+hw)*4;\n" +" \n" +" float4 valueL=convert_float4(vload4(0,input+in_offset));\n" +" float4 valueR=convert_float4(vload4(shape.z,input+in_offset));\n" +" #ifdef DOUBLE_INPUTS\n" +" float valueConstL=input1[hw];\n" +" float valueConstR=input1[shape.z+hw];\n" +" valueL += (float4)valueConstL;\n" +" valueR += (float4)valueConstR;\n" +" #endif\n" +" float4 out=(erf(valueR*(float4)0.7071067932881648)+(float4)1.0)*valueR*(float4)0.5;\n" +" out *= valueL;\n" +" vstore4(CONVERT_FLOAT4(out),0,output+out_offset);\n" +"#endif\n" +" }\n" +"}\n" +; #endif -{ - "grid_sample", - { 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} - }, #ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "gemm_buf", - { 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} - }, +const char* select_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__kernel void select_buf(GLOBAL_SIZE_2_DIMS\n" +" __global const int* select,\n" +" __global const FLOAT* input0,\n" +" __global const FLOAT* input1,\n" +" __global FLOAT* output\n" +" ) {\n" +" const int idx=get_global_id(0);\n" +" const int idy=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(idx,idy);\n" +" if (select[idx]) {\n" +"#ifdef INSIZE1_EUQAL_1\n" +" output[idx]=input0[0];\n" +"#else\n" +" output[idx]=input0[idx];\n" +"#endif\n" +" } else {\n" +"#ifdef INSIZE2_EUQAL_1\n" +" output[idx]=input1[0];\n" +"#else\n" +" output[idx]=input1[idx];\n" +"#endif\n" +" }\n" +"}\n" +; #endif -{ - "copy_buffer_to_image2d", - { 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} - }, +const char* grid_sample = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"enum BorderMode {\n" +" BorderMode_ZEROS=0,\n" +" BorderMode_CLAMP=1,\n" +" BorderMode_REFLECTION=2,\n" +" BorderMode_MIN=BorderMode_ZEROS,\n" +" BorderMode_MAX=BorderMode_REFLECTION\n" +"};\n" +"float getPosition(float x,int range,int alignCorners){\n" +" float a=alignCorners == 1? 1.0f : 0.0f;\n" +" float b=alignCorners == 1? 0.0f : 1.0f;\n" +" return ((1+x)*(range-a)-b)/2.0f;\n" +"}\n" +"static int CLAMP(int v,int min,int max) {\n" +" if ((v)max) {\n" +" (v)=max;\n" +" }\n" +" return v;\n" +"}\n" +"FLOAT4 sample(int h,int w,\n" +" const int w_offset_base,\n" +" const int h_offset_base,\n" +" __read_only image2d_t tmp,\n" +" int height,int width,\n" +" enum BorderMode paddingMode){\n" +" if (h<0 || h >= height || w<0 || w >= width) {\n" +" if(paddingMode == BorderMode_ZEROS)\n" +" {\n" +" return 0.0f;\n" +" }\n" +" // Clearly,CLAMP is the right way to go for GridSamplePaddingMode_BORDER\n" +" // For GridSamplePaddingMode_REFLECTION,since we have reflected the values into (-1,1),\n" +" // the leftover reflections degrade to GridSamplePaddingMode_BORDER\n" +" h=CLAMP(h,0,height-1);\n" +" w=CLAMP(w,0,width-1);\n" +" }\n" +" return RI_F(tmp,SAMPLER,(int2)(w_offset_base+w,h_offset_base+h));\n" +"}\n" +"__kernel void nearest(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,\n" +" __read_only image2d_t grid,\n" +" __write_only image2d_t output,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int output_height,\n" +" __private const int output_width,\n" +" __private const enum BorderMode paddingMode,\n" +" __private const int alignCorners\n" +" ){\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_batch_idx=output_batch_height_block_idx/output_height;\n" +" const int output_height_idx=output_batch_height_block_idx % output_height;\n" +" // grid data format has been converted from nchw to nc4hw4\n" +" /* slice slice\n" +" (x1,y1)...(xn,y1) (x1,x1,x1,x1) (y1,y2,y3,y4) | (x1,x1,x1,x1) (y5,y6,y7,y8) | ... \n" +" . . . . | . . |\n" +" . . <-> . . | . . |\n" +" . . . . | . . |\n" +" (x1,ym)...(xn,ym) (xn,xn,xn,xn) (y1,y2,y3,y4) | (xn,xn,xn,xn) (y5,y6,y7,y8) | ...\n" +" */\n" +" const int slice=output_height_idx/4;\n" +" const int grid_w_offset=0;\n" +" const int grid_h_offset=mad24(output_batch_idx,output_width,output_width_block_idx);\n" +" \n" +" FLOAT4 grid_x=RI_F(grid,SAMPLER,(int2)(grid_w_offset+2*slice,grid_h_offset));\n" +" FLOAT4 grid_y=RI_F(grid,SAMPLER,(int2)(grid_w_offset+1+2*slice,grid_h_offset));\n" +" const float arr[8]={grid_x.x,grid_y.x,grid_x.y,grid_y.y,grid_x.z,grid_y.z,grid_x.w,grid_y.w};\n" +" \n" +" // get grid x,y\n" +" const int arr_offset=output_height_idx % 4;\n" +" const float x=arr[2*arr_offset];\n" +" const float y=arr[2*arr_offset+1];\n" +" // convert grid x,y to input coordinate range\n" +" float in_grid_x=getPosition(x,input_width,alignCorners);\n" +" float in_grid_y=getPosition(y,input_height,alignCorners);\n" +" // get nearest point\n" +" int nw=floor(in_grid_x+0.5f);\n" +" int nh=floor(in_grid_y+0.5f);\n" +" const int inp_w_offset=mul24(output_channel_block_idx,input_width);\n" +" const int inp_h_offset=mul24(output_batch_idx,input_height);\n" +" FLOAT4 value=sample(nh,nw,inp_w_offset,inp_h_offset,input,input_height,input_width,paddingMode);\n" +" const int output_w_offset=mad24(output_channel_block_idx,output_width,output_width_block_idx);\n" +" const int output_h_offset=mad24(output_batch_idx,output_height,output_height_idx);\n" +" WI_F(output,(int2)(output_w_offset,output_h_offset),value);\n" +"}\n" +"__kernel void bilinear(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,\n" +" __read_only image2d_t grid,\n" +" __write_only image2d_t output,\n" +" __private const int input_height,\n" +" __private const int input_width,\n" +" __private const int output_height,\n" +" __private const int output_width,\n" +" __private const enum BorderMode paddingMode,\n" +" __private const int alignCorners\n" +" ){\n" +" const int output_channel_block_idx=get_global_id(0);\n" +" const int output_width_block_idx=get_global_id(1);\n" +" const int output_batch_height_block_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_block_idx,output_width_block_idx,output_batch_height_block_idx);\n" +" const int output_batch_idx=output_batch_height_block_idx/output_height;\n" +" const int output_height_idx=output_batch_height_block_idx % output_height;\n" +" // get grid idx\n" +" const int slice=output_height_idx/4;\n" +" const int grid_w_offset=0;\n" +" const int grid_h_offset=mad24(output_batch_idx,output_width,output_width_block_idx);\n" +" \n" +" FLOAT4 grid_x=RI_F(grid,SAMPLER,(int2)(grid_w_offset+2*slice,grid_h_offset));\n" +" FLOAT4 grid_y=RI_F(grid,SAMPLER,(int2)(grid_w_offset+1+2*slice,grid_h_offset));\n" +" const float arr[8]={grid_x.x,grid_y.x,grid_x.y,grid_y.y,grid_x.z,grid_y.z,grid_x.w,grid_y.w};\n" +" \n" +" // get grid x,y\n" +" const int arr_offset=output_height_idx % 4;\n" +" const float x=arr[2*arr_offset];\n" +" const float y=arr[2*arr_offset+1];\n" +" // convert grid x,y to input coordinate range\n" +" float in_grid_x=getPosition(x,input_width,alignCorners);\n" +" float in_grid_y=getPosition(y,input_height,alignCorners);\n" +" int in_h0=floor(in_grid_y);\n" +" int in_w0=floor(in_grid_x);\n" +" int in_h1=ceil(in_grid_y);\n" +" int in_w1=ceil(in_grid_x);\n" +" float x_weight=in_w1-in_grid_x;\n" +" float y_weight=in_h1-in_grid_y;\n" +" const int inp_w_offset=mul24(output_channel_block_idx,input_width);\n" +" const int inp_h_offset=mul24(output_batch_idx,input_height);\n" +" FLOAT4 i00=sample(in_h0,in_w0,inp_w_offset,inp_h_offset,input,input_height,input_width,paddingMode);\n" +" FLOAT4 i01=sample(in_h0,in_w1,inp_w_offset,inp_h_offset,input,input_height,input_width,paddingMode);\n" +" FLOAT4 i10=sample(in_h1,in_w0,inp_w_offset,inp_h_offset,input,input_height,input_width,paddingMode);\n" +" FLOAT4 i11=sample(in_h1,in_w1,inp_w_offset,inp_h_offset,input,input_height,input_width,paddingMode);\n" +" // bilinear interpolation\n" +" FLOAT4 value=CONVERT_FLOAT4(((FLOAT4)x_weight*CONVERT_FLOAT4(i00)+(FLOAT4)(1.0f-x_weight)*CONVERT_FLOAT4(i01))*(FLOAT4)y_weight +\n" +" ((FLOAT4)x_weight*CONVERT_FLOAT4(i10)+(FLOAT4)(1.0f-x_weight)*CONVERT_FLOAT4(i11))*(FLOAT4)(1.0f- y_weight));\n" +" const int output_w_offset=mad24(output_channel_block_idx,output_width,output_width_block_idx);\n" +" const int output_h_offset=mad24(output_batch_idx,output_height,output_height_idx);\n" +" WI_F(output,(int2)(output_w_offset,output_h_offset),value);\n" +"}\n" +; +const char* buffer_convert_quant = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"#ifdef USE_LOW_BIT_WEIGHT_INT8\n" +"// convert kernel : from int8 buffer(oihw) to int8 image(oc/4 h w ,ic oc4)\n" +"__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int8(GLOBAL_SIZE_2_DIMS\n" +" __global const char *input_ptr,\n" +" __private const int output_channel,\n" +" __private const int2 kernel_shape,\n" +" __private const int ic_h_w_size,\n" +" __private const int height_width_size,\n" +" __global char *output) {\n" +" int image_width_idx=get_global_id(0); // ic\n" +" int image_height_idx=get_global_id(1); // oc/4 h w\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" \n" +" const int input_channel_4_idx=image_width_idx;\n" +" const int output_channel_4_idx=(image_height_idx/height_width_size)*4;\n" +" const int height_width_idx=image_height_idx % height_width_size;\n" +" const int buffer_height_idx=height_width_idx/kernel_shape.y;\n" +" const int buffer_width_idx=height_width_idx % kernel_shape.y;\n" +" \n" +" const int buffer_offset=output_channel_4_idx*ic_h_w_size+input_channel_4_idx*height_width_size +\n" +" buffer_height_idx*kernel_shape.y+buffer_width_idx;\n" +" \n" +" char4 output_values=0;\n" +" if (output_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(char)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(char)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(char)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.w=(char)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(char)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(char)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(char)(*(input_ptr+offset));\n" +" \n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(char)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(char)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(char)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" const int out_offset=(image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*4;\n" +" vstore4(output_values,0,output+out_offset);\n" +"}\n" +"#endif\n" +"#ifdef USE_LOW_BIT_WEIGHT_INT4\n" +"// convert kernel : from int8 buffer(oihw) to int4 image(oc/4 h w ,ic oc4)\n" +"__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_int4(GLOBAL_SIZE_2_DIMS\n" +" __global const char *input_ptr,\n" +" __private const int output_channel,\n" +" __private const int2 kernel_shape,\n" +" __private const int ic_h_w_size,\n" +" __private const int height_width_size,\n" +" __global uchar *output) {\n" +" int image_width_idx=get_global_id(0); // ic\n" +" int image_height_idx=get_global_id(1); // oc/4 h w\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" \n" +" const int input_channel_4_idx=image_width_idx;\n" +" const int output_channel_4_idx=(image_height_idx/height_width_size)*4;\n" +" const int height_width_idx=image_height_idx % height_width_size;\n" +" const int buffer_height_idx=height_width_idx/kernel_shape.y;\n" +" const int buffer_width_idx=height_width_idx % kernel_shape.y;\n" +" \n" +" const int buffer_offset=output_channel_4_idx*ic_h_w_size+input_channel_4_idx*height_width_size +\n" +" buffer_height_idx*kernel_shape.y+buffer_width_idx;\n" +" \n" +" char4 output_values_int8=0;\n" +" if (output_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values_int8.x=(char)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values_int8.y=(char)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values_int8.z=(char)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values_int8.w=(char)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values_int8.x=(char)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values_int8.y=(char)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values_int8.z=(char)(*(input_ptr+offset));\n" +" \n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values_int8.x=(char)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values_int8.y=(char)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values_int8.x=(char)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" \n" +" uchar2 output_values_int4=(uchar2)(0,0);\n" +" output_values_int4.s0=(output_values_int8.x+8)*16+(output_values_int8.y+8);\n" +" output_values_int4.s1=(output_values_int8.z+8)*16+(output_values_int8.w+8);\n" +" \n" +" const int out_offset=(image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*2;\n" +" vstore2(output_values_int4,0,output+out_offset);\n" +"}\n" +"#endif\n" +"#define CHAR16_TO_UCHAR8(a, b) "" a=(uchar8)(((b.s0+8) << 4)+b.s1+8,((b.s2+8) << 4)+b.s3+8,((b.s4+8) << 4)+b.s5+8,((b.s6+8) << 4)+b.s7+8,((b.s8+8) << 4)+b.s9+8,((b.sa+8) << 4)+b.sb+8,((b.sc+8) << 4)+b.sd+8,((b.se+8) << 4)+b.sf+8);\n" +"#define CHAR32_TO_UCHAR16(a, b, c) "" a = (uchar16)(((b.s0 + 8) << 4) + b.s1 + 8, ((b.s2 + 8) << 4) + b.s3 + 8, ((b.s4 + 8) << 4) + b.s5 + 8, ((b.s6 + 8) << 4) + b.s7 + 8, ((b.s8 + 8) << 4) + b.s9 + 8, ((b.sa + 8) << 4) + b.sb + 8, ((b.sc + 8) << 4) + b.sd + 8, ((b.se + 8) << 4) + b.sf + 8, "" ((c.s0+8) << 4)+c.s1+8,((c.s2+8) << 4)+c.s3+8,((c.s4+8) << 4)+c.s5+8,((c.s6+8) << 4)+c.s7+8,((c.s8+8) << 4)+c.s9+8,((c.sa+8) << 4)+c.sb+8,((c.sc+8) << 4)+c.sd+8,((c.se+8) << 4)+c.sf+8);\n" +"__kernel void conv2d_1x1_weight_quant_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const char *input_ptr,\n" +"#ifdef USE_LOW_BIT_WEIGHT_INT4\n" +" __global uchar *output_ptr,\n" +"#else\n" +" __global char *output_ptr,\n" +"#endif\n" +" __private const int input_channel,\n" +" __private const int output_channel) {\n" +" int x=get_global_id(0); // ic/16\n" +" int y=get_global_id(1); // oc\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(x,y);\n" +" const int xin=x << 4;\n" +" const int outputChannelC4=(output_channel+3) >> 2;\n" +" const int inputOffset=y*input_channel+xin;\n" +" char16 weight=0;\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" if(xin+15 >= input_channel){\n" +" char *weight_ptr=(char*)&weight;\n" +" for(int i=0,j=0; xin+i> 2;\n" +" const int xin=x << 5;\n" +" const int inputOffset=y*input_channel+xin;\n" +" char16 weight00=0,weight01=0;\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" if(xin+31 >= input_channel){\n" +" char *weight00_ptr=(char*)&weight00;\n" +" char *weight01_ptr=(char*)&weight01;\n" +" int i=0;\n" +" for(int j=0; xin+i> 2;\n" +" char16 weight=0;\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" if(xin+15 >= input_channel){\n" +" char *weight_ptr=(char*)&weight;\n" +" for(int i=0,j=0; xin+i= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +"__kernel void gemm_buf(GLOBAL_SIZE_DIM2\n" +" __global const FLOAT* input0,\n" +" __global const FLOAT* input1,\n" +" __global FLOAT* output,\n" +" __private const int width,//UP_DIV(wUnit*hUnit,4)\n" +" __private const int height,//dstChannelC4\n" +" __private const int srcChannelC4,\n" +" __private const int alpha2) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" const int pos_x=pos.x % width;\n" +" const int pos_y=pos.x/width;\n" +" const int pos_z=pos.y;\n" +" COMPUTE_FLOAT16 o=(COMPUTE_FLOAT16)0;\n" +" \n" +" int kenerlY=mad24(pos_z,height,pos_y);\n" +" for (int k=0; k> 1;\n" +" const int pos_x=(pos.x % width_block) << 1;\n" +" const int pos_y=pos.x/width_block;\n" +" const int pos_z=pos.y;\n" +" COMPUTE_FLOAT16 o0=(COMPUTE_FLOAT16)0;\n" +" COMPUTE_FLOAT16 o1=(COMPUTE_FLOAT16)0;\n" +" const int kenerlY=mad24(pos_z,height,pos_y);\n" +" const int kernel_base=mul24(kenerlY,srcChannelC4);\n" +" const int inp_base=(pos_z*srcChannelC4+0)*width+pos_x;\n" +" \n" +" for (int k=0; k= width) return;\n" +" vstore4(CONVERT_FLOAT4(o1.s0123),1,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(o1.s4567),1,output+out_offset+4*width);\n" +" vstore4(CONVERT_FLOAT4(o1.s89ab),1,output+out_offset+8*width);\n" +" vstore4(CONVERT_FLOAT4(o1.scdef),1,output+out_offset+12*width);\n" +"}\n" +"// [M,K/4,4] -> [alignK,alignM]\n" +"__kernel void transpose_pad(GLOBAL_SIZE_DIM2\n" +" const int alignM,\n" +" const int alignK,\n" +" const int M,\n" +" const int K,\n" +" __global const FLOAT* input,\n" +" __global FLOAT* output\n" +" ) {\n" +" const int idx_m4=get_global_id(0); // idx M\n" +" const int idx_k4=get_global_id(1); // idx K\n" +" UNIFORM_BOUNDRY_CHECK(idx_m4,idx_k4);\n" +" const int idx_m=idx_m4 << 2;\n" +" const int idx_k=idx_k4 << 2;\n" +" const int K_4=(K+3) >> 2;\n" +" const int in_offset_base=(idx_m*K_4+idx_k4)*4;\n" +" const int out_offset_base=idx_k*alignM+idx_m;\n" +" \n" +" FLOAT4 m0k4=(idx_k4 >= K_4 || idx_m+0 >= M) ? (FLOAT4)0 : vload4(0,input+in_offset_base);\n" +" FLOAT4 m1k4=(idx_k4 >= K_4 || idx_m+1 >= M) ? (FLOAT4)0 : vload4(0,input+in_offset_base+(K_4 << 2));\n" +" FLOAT4 m2k4=(idx_k4 >= K_4 || idx_m+2 >= M) ? (FLOAT4)0 : vload4(0,input+in_offset_base+(K_4 << 2)*2);\n" +" FLOAT4 m3k4=(idx_k4 >= K_4 || idx_m+3 >= M) ? (FLOAT4)0 : vload4(0,input+in_offset_base+(K_4 << 2)*3);\n" +" \n" +" vstore4((FLOAT4)(m0k4.x,m1k4.x,m2k4.x,m3k4.x),0,output+out_offset_base);\n" +" vstore4((FLOAT4)(m0k4.y,m1k4.y,m2k4.y,m3k4.y),0,output+out_offset_base+alignM);\n" +" vstore4((FLOAT4)(m0k4.z,m1k4.z,m2k4.z,m3k4.z),0,output+out_offset_base+alignM+alignM);\n" +" vstore4((FLOAT4)(m0k4.w,m1k4.w,m2k4.w,m3k4.w),0,output+out_offset_base+alignM+alignM+alignM);\n" +"}\n" +"// [alignM,alignN] -> [M,N/4,4]\n" +"__kernel void add_bias(GLOBAL_SIZE_DIM2\n" +" const int alignM,\n" +" const int alignN,\n" +" const int M,\n" +" const int N,\n" +" __global const FLOAT* input0,\n" +" __global const FLOAT* input1,\n" +" __global FLOAT* output\n" +" ) {\n" +" const int idx_m=get_global_id(0); // idx M\n" +" const int idx_n_16=get_global_id(1); // idx N\n" +" UNIFORM_BOUNDRY_CHECK(idx_m,idx_n_16);\n" +" const int N_16=(N+15) >> 4;\n" +" const int N_left=N & 15;\n" +" bool canVec16=(N_left == 0 || (N_left != 0 && idx_n_16> 2;\n" +" FLOAT4 res0=vload4(0,input0+idx_m*alignN+(idx_n_16 << 4));\n" +" FLOAT4 res1=vload4(0,input1+(idx_n_16 << 4));\n" +" FLOAT4 res=res0+res1;\n" +" vstore4(res,0,output+((idx_m*N_16+idx_n_16) << 4));\n" +" \n" +" if(idx_n_16*4+1 >= N_4) return;\n" +" res0=vload4(0,input0+idx_m*alignN+(idx_n_16 << 4)+4);\n" +" res1=vload4(0,input1+(idx_n_16 << 4)+4);\n" +" res=res0+res1;\n" +" vstore4(res,0,output+((idx_m*N_16+idx_n_16) << 4)+4);\n" +" \n" +" if(idx_n_16*4+2 >= N_4) return;\n" +" res0=vload4(0,input0+idx_m*alignN+(idx_n_16 << 4)+8);\n" +" res1=vload4(0,input1+(idx_n_16 << 4)+8);\n" +" res=res0+res1;\n" +" vstore4(res,0,output+((idx_m*N_16+idx_n_16) << 4)+8);\n" +" \n" +" if(idx_n_16*4+3 >= N_4) return;\n" +" res0=vload4(0,input0+idx_m*alignN+(idx_n_16 << 4)+12);\n" +" res1=vload4(0,input1+(idx_n_16 << 4)+12);\n" +" res=res0+res1;\n" +" vstore4(res,0,output+((idx_m*N_16+idx_n_16) << 4)+12);\n" +" }\n" +"}\n" +; +#endif +const char* copy_buffer_to_image2d = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void copy_buffer_to_image2d(\n" +" #ifdef BUFFER_INP_FP32\n" +" __global const float4* input,\n" +" #else\n" +" __global const FLOAT4* input,\n" +" #endif\n" +" __write_only image2d_t uOutput,\n" +" __private const int width,__private const int height) {\n" +" int x=get_global_id(0);\n" +" int y=get_global_id(1);\n" +" if (x= 0) {\n" +" index.x=offset_O[pos.z];\n" +" }\n" +" if (iters.y >= 0) {\n" +" index.y=offset_A[pos.z];\n" +" }\n" +" if (iters.z >= 0) {\n" +" index.z=offset_B[pos.z];\n" +" }\n" +"#ifdef BIAS\n" +" if (iters.w >= 0) {\n" +" index.w=offset_C[pos.z];\n" +" }\n" +"#endif\n" +" int4 offset=index*steps+offsets;\n" +" \n" +"#if TRANSPOSE_A\n" +" __global FLOAT* A_ptr=input_A+offset.y+pos.y;\n" +"#else\n" +" __global FLOAT* A_ptr=input_A+offset.y+pos.y*l;\n" +"#endif\n" +"#if TRANSPOSE_B\n" +" __global FLOAT* B_ptr=input_B+offset.z+pos.x*l;\n" +"#else\n" +" __global FLOAT* B_ptr=input_B+offset.z+pos.x;\n" +"#endif\n" +"#ifdef BIAS\n" +" FLOAT4 value0=vload4(0,input_C+offset.w+pos.x);\n" +" FLOAT4 value1=value0;\n" +" FLOAT4 value2=value0;\n" +" FLOAT4 value3=value0;\n" +"#else\n" +" FLOAT4 value0=(FLOAT4)0;\n" +" FLOAT4 value1=(FLOAT4)0;\n" +" FLOAT4 value2=(FLOAT4)0;\n" +" FLOAT4 value3=(FLOAT4)0;\n" +"#endif\n" +" const int l_pack=(l+3) >> 2;\n" +" for(int i=0; i= e) return;\n" +" vstore4(value1,0,output+output_offset+h);\n" +" if(pos.y+2 >= e) return;\n" +" vstore4(value2,0,output+output_offset+2*h);\n" +" if(pos.y+3 >= e) return;\n" +" vstore4(value3,0,output+output_offset+3*h);\n" +"#else\n" +" if(pos.x+3= e) return;\n" +" vstore4(value1,0,output+output_offset+h);\n" +" if(pos.y+2 >= e) return;\n" +" vstore4(value2,0,output+output_offset+2*h);\n" +" if(pos.y+3 >= e) return;\n" +" vstore4(value3,0,output+output_offset+3*h);\n" +" }else{\n" +"#if H_LEAVES == 1\n" +" output[output_offset]=value0.x;\n" +" if(pos.y+1 >= e) return;\n" +" output[output_offset+h]=value1.x;\n" +" if(pos.y+2 >= e) return;\n" +" output[output_offset+2*h]=value2.x;\n" +" if(pos.y+3 >= e) return;\n" +" output[output_offset+3*h]=value3.x;\n" +"#elif H_LEAVES == 2\n" +" vstore2((FLOAT2)value0.xy,0,output+output_offset);\n" +" if(pos.y+1 >= e) return;\n" +" vstore2((FLOAT2)value1.xy,0,output+output_offset+h);\n" +" if(pos.y+2 >= e) return;\n" +" vstore2((FLOAT2)value2.xy,0,output+output_offset+2*h);\n" +" if(pos.y+3 >= e) return;\n" +" vstore2((FLOAT2)value3.xy,0,output+output_offset+3*h);\n" +"#elif H_LEAVES == 3\n" +" vstore3((FLOAT3)value0.xyz,0,output+output_offset);\n" +" if(pos.y+1 >= e) return;\n" +" vstore3((FLOAT3)value1.xyz,0,output+output_offset+h);\n" +" if(pos.y+2 >= e) return;\n" +" vstore3((FLOAT3)value2.xyz,0,output+output_offset+2*h);\n" +" if(pos.y+3 >= e) return;\n" +" vstore3((FLOAT3)value3.xyz,0,output+output_offset+3*h);\n" +"#endif\n" +" }\n" +"#endif\n" +" }\n" +"}\n" +"__kernel void tile(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __read_only image2d_t input,\n" +" __global OUTPUT_TYPE* output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel){\n" +" int3 pos=(int3)(get_global_id(0),get_global_id(1),get_global_id(2));\n" +" if (pos.x= channel)return;\n" +" dst_ptr[c_dst_pitch]=value.y;\n" +" if(c+2 >= channel)return;\n" +" dst_ptr[2*c_dst_pitch]=value.z;\n" +" if(c+3 >= channel)return;\n" +" dst_ptr[3*c_dst_pitch]=value.w;\n" +" }\n" +"}\n" +"__kernel void pack(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input,\n" +" __write_only image2d_t output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel){\n" +" int3 pos=(int3)(get_global_id(0),get_global_id(1),get_global_id(2));\n" +" if (pos.x= 0) {\n" +" index.x=offset_dst[pos.z];\n" +" }\n" +" if (iters.y >= 0) {\n" +" index.y=offset_src[pos.z];\n" +" }\n" +" int2 offset=index*steps;\n" +" if(offset.x >= 0){\n" +" if(offset.y >= 0 && offset.y= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"#define ARGMAX_SELECT(A, B, C, D) "" if(A.x < B.x){ A.x = B.x; C.x = D; } "" if(A.y < B.y){ A.y = B.y; C.y = D; } "" if(A.z < B.z){ A.z = B.z; C.z = D; } "" if(A.w B.x){ A.x = B.x; C.x = D; } "" if(A.y > B.y){ A.y = B.y; C.y = D; } "" if(A.z > B.z){ A.z = B.z; C.z = D; } "" if(A.w>B.w){ A.w=B.w; C.w=D; } \n" +"__kernel void argmax_width_buf(GLOBAL_SIZE_3_DIMS\n" +" __global const FLOAT* input,\n" +" __global int* output,\n" +" __private const int inputWidth,\n" +" __private const int inputHeight,\n" +" __private const int inputChannel,\n" +" __private const int inputBatch,\n" +" __private const int inputChannelBlock,\n" +" __private const int oututWidth,\n" +" __private const int outputHeight,\n" +" __private const int outputChannel,\n" +" __private const int outputChannelBlock\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(x,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/outputChannelBlock;\n" +" const int channel_idx=batch_channel_idx % outputChannelBlock;\n" +" \n" +" const int offset=((((batch_idx*inputChannelBlock)+channel_idx)*inputHeight+height_idx)*inputWidth+0)*4;\n" +" const int outputOffset=((((batch_idx*outputChannelBlock)+channel_idx)*outputHeight+height_idx)*oututWidth+0)*4;\n" +" int4 index=0;\n" +"#ifdef ARGMAX\n" +" FLOAT4 maxValue=(FLOAT4)-FLT_MAX;\n" +"#else\n" +" FLOAT4 maxValue=(FLOAT4)FLT_MAX;\n" +"#endif\n" +"#if ARGMAX_LOCAL_SIZE >= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT4 local reduce[ARGMAX_LOCAL_SIZE];\n" +" int4 local index_reduce[ARGMAX_LOCAL_SIZE];\n" +" \n" +" for (int i=lid; i0; i /= 2){\n" +" if (lidreduce[lid+i].x){reduce[lid].x=reduce[lid+i].x; index_reduce[lid].x=index_reduce[lid+i].x;}\n" +" if(reduce[lid].y>reduce[lid+i].y){reduce[lid].y=reduce[lid+i].y; index_reduce[lid].y=index_reduce[lid+i].y;}\n" +" if(reduce[lid].z>reduce[lid+i].z){reduce[lid].z=reduce[lid+i].z; index_reduce[lid].z=index_reduce[lid+i].z;}\n" +" if(reduce[lid].w>reduce[lid+i].w){reduce[lid].w=reduce[lid+i].w; index_reduce[lid].w=index_reduce[lid+i].w;}\n" +"#endif\n" +" }\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" }\n" +" if(lid == 0){\n" +" vstore4(index_reduce[0],0,output+outputOffset);\n" +" }\n" +"#else\n" +" for(int i=0; i= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT4 local reduce[ARGMAX_LOCAL_SIZE];\n" +" int4 local index_reduce[ARGMAX_LOCAL_SIZE];\n" +" \n" +" for (int i=lid; i0; i /= 2){\n" +" if (lidreduce[lid+i].x){reduce[lid].x=reduce[lid+i].x; index_reduce[lid].x=index_reduce[lid+i].x;}\n" +" if(reduce[lid].y>reduce[lid+i].y){reduce[lid].y=reduce[lid+i].y; index_reduce[lid].y=index_reduce[lid+i].y;}\n" +" if(reduce[lid].z>reduce[lid+i].z){reduce[lid].z=reduce[lid+i].z; index_reduce[lid].z=index_reduce[lid+i].z;}\n" +" if(reduce[lid].w>reduce[lid+i].w){reduce[lid].w=reduce[lid+i].w; index_reduce[lid].w=index_reduce[lid+i].w;}\n" +"#endif\n" +" }\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" }\n" +" if(lid == 0){\n" +" vstore4(index_reduce[0],0,output+outputOffset);\n" +" }\n" +"#else\n" +" for(int i=0; i= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT local reduce[ARGMAX_LOCAL_SIZE];\n" +" int local index_reduce[ARGMAX_LOCAL_SIZE];\n" +" \n" +" for (int i=lid; ivaluePtr[j]){\n" +" index=i*4+j;\n" +" maxValue=valuePtr[j];\n" +" }\n" +"#endif\n" +" }\n" +" }\n" +" reduce[lid]=maxValue;\n" +" index_reduce[lid]=index;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=ARGMAX_LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (lidreduce[lid+i]){reduce[lid]=reduce[lid+i]; index_reduce[lid]=index_reduce[lid+i];}\n" +"#endif\n" +" }\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" }\n" +" if(lid == 0){\n" +" maxValue=reduce[lid];\n" +" index=index_reduce[lid];\n" +" value=vload4((inputChannelBlock-1)*inputWidth*inputHeight,input+offset);\n" +" for(int j=0; jvaluePtr[j]){\n" +" index=(inputChannelBlock-1)*4+j;\n" +" maxValue=valuePtr[j];\n" +" }\n" +"#endif\n" +" }\n" +" output[outputOffset]=index;\n" +" }\n" +"#else\n" +" for(int i=0; ivaluePtr[j]){\n" +" index=i*4+j;\n" +" maxValue=valuePtr[j];\n" +" }\n" +"#endif\n" +" }\n" +" }\n" +" value=vload4((inputChannelBlock-1)*inputWidth*inputHeight,input+offset);\n" +" for(int j=0; jvaluePtr[j]){\n" +" index=(inputChannelBlock-1)*4+j;\n" +" maxValue=valuePtr[j];\n" +" }\n" +"#endif\n" +" }\n" +" output[outputOffset]=index;\n" +"#endif\n" +"}\n" +"__kernel void argmax_batch_buf(GLOBAL_SIZE_3_DIMS\n" +" __global const FLOAT* input,\n" +" __global int* output,\n" +" __private const int inputWidth,\n" +" __private const int inputHeight,\n" +" __private const int inputChannel,\n" +" __private const int inputBatch,\n" +" __private const int inputChannelBlock,\n" +" __private const int oututWidth,\n" +" __private const int outputHeight,\n" +" __private const int outputChannel,\n" +" __private const int outputChannelBlock\n" +" ) {\n" +" const int x=get_global_id(0);\n" +" const int wh=get_global_id(1);\n" +" const int channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(x,wh,channel_idx);\n" +" \n" +" const int width_idx=wh % oututWidth;\n" +" const int height_idx=wh/oututWidth;\n" +" const int offset=((((0*inputChannelBlock)+channel_idx)*inputHeight+height_idx)*inputWidth+width_idx)*4;\n" +" const int outputOffset=((((0*outputChannelBlock)+channel_idx)*outputHeight+height_idx)*oututWidth+width_idx)*4;\n" +" int4 index=0;\n" +" int batchOffset=inputChannelBlock*inputHeight*inputWidth;\n" +"#ifdef ARGMAX\n" +" FLOAT4 maxValue=(FLOAT4)-FLT_MAX;\n" +"#else\n" +" FLOAT4 maxValue=(FLOAT4)FLT_MAX;\n" +"#endif\n" +"#if ARGMAX_LOCAL_SIZE >= 4\n" +" int lid=get_local_id(0);\n" +" FLOAT4 local reduce[ARGMAX_LOCAL_SIZE];\n" +" int4 local index_reduce[ARGMAX_LOCAL_SIZE];\n" +" \n" +" for (int i=lid; i0; i /= 2){\n" +" if (lidreduce[lid+i].x){reduce[lid].x=reduce[lid+i].x; index_reduce[lid].x=index_reduce[lid+i].x;}\n" +" if(reduce[lid].y>reduce[lid+i].y){reduce[lid].y=reduce[lid+i].y; index_reduce[lid].y=index_reduce[lid+i].y;}\n" +" if(reduce[lid].z>reduce[lid+i].z){reduce[lid].z=reduce[lid+i].z; index_reduce[lid].z=index_reduce[lid+i].z;}\n" +" if(reduce[lid].w>reduce[lid+i].w){reduce[lid].w=reduce[lid+i].w; index_reduce[lid].w=index_reduce[lid+i].w;}\n" +"#endif\n" +" }\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" }\n" +" if(lid == 0){\n" +" vstore4(index_reduce[0],0,output+outputOffset);\n" +" }\n" +"#else\n" +" for(int i=0; i= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"// convert data from buffer(nhwc) to buffer(nc16hw16) float input\n" +"__kernel void nhwc_buffer_to_nc16hw16_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int height,\n" +" __private const int width,__private const int channels,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int input_pad_left,__private const int input_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_16_idx=(image_width_idx/width) << 4;\n" +" const int buffer_offset=((batch_idx*height+height_idx)*width+width_idx)*channels+channel_16_idx;\n" +" const int remain_channel=min(channels-channel_16_idx,16);\n" +" INPUT_TYPE16 values=0;\n" +" INPUT_TYPE* values_ptr=(INPUT_TYPE*)(&values);\n" +" __global const INPUT_TYPE *input_current_ptr=input_ptr+buffer_offset;\n" +" for(int i=0; i= src_bc_offset.x ? (INPUT_TYPE4)0 : vload4(0,input_ptr+src_buffer_offset+width_height_size4);\n" +" INPUT_TYPE4 values2=in_channel_block_idx+2 >= src_bc_offset.x ? (INPUT_TYPE4)0 : vload4(0,input_ptr+src_buffer_offset+width_height_size4*2);\n" +" INPUT_TYPE4 values3=in_channel_block_idx+3 >= src_bc_offset.x ? (INPUT_TYPE4)0 : vload4(0,input_ptr+src_buffer_offset+width_height_size4*3);\n" +" \n" +" vstore16(CONVERT_OUTPUT16((INPUT_TYPE16)(values0.s0123,values1.s0123,values2.s0123,values3.s0123)),0,output+dst_buffer_offset);\n" +" if(width_idx == 0){\n" +" int pad_offset=(((dst_bc_offset.x+dst_bc_offset.y)*output_shape.x+height_idx)*dst_width)*16;\n" +" for(int i=0; i= channelc4) return;\n" +" vstore4(CONVERT_OUTPUT4(values.s4567),0,output+dst_buffer_offset+width_height_size4);\n" +" if(out_channel_block_idx+2 >= channelc4) return;\n" +" vstore4(CONVERT_OUTPUT4(values.s89ab),0,output+dst_buffer_offset+2*width_height_size4);\n" +" if(out_channel_block_idx+3 >= channelc4) return;\n" +" vstore4(CONVERT_OUTPUT4(values.scdef),0,output+dst_buffer_offset+3*width_height_size4);\n" +"}\n" +; +#endif #endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* attention_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void matmul_qk_div_mask(GLOBAL_SIZE_3_DIMS\n" +" __global const FLOAT *input0,// query [1 query_seq_len/4 head_num head_dim 4]\n" +" __global const FLOAT *input1,// key [1 key_seq_len/4 head_num head_dim 4]\n" +" __global FLOAT *output,// prefill [1 head_num query_seq_len/4 key_seq_len 4] decode[1 head_num key_seq_len/4 4]\n" +" __global FLOAT *past_key,// [1 head_num max_length/4 head_dim 4]\n" +"#ifdef ADD_MASK\n" +" __global const FLOAT* mask,\n" +"#else\n" +" __global const int* mask,// [1 1 query_seq_len key_seq_len 4]\n" +"#endif\n" +" __private const float scale,\n" +" __private const int query_seq_len,\n" +" __private const int key_seq_len,\n" +" __private const int head_num,\n" +" __private const int kv_head_num,\n" +" __private const int head_dim) {\n" +" const int x=get_global_id(0); // query_seq_len/4 for prefill 1 for decode\n" +" const int y=get_global_id(1); // head_num\n" +" const int z=get_global_id(2); // key_seq_len/4\n" +" DEAL_NON_UNIFORM_DIM3(x,y,z);\n" +" \n" +" int yin=y/NUMHEAD_GROUP_SIZE;\n" +" const int offset=head_num*head_dim*4;\n" +" const int offset_head=y*head_dim*4;\n" +" __global const FLOAT *A_offset=input0+x*offset+offset_head;\n" +" __global FLOAT *Pastkey_offset=past_key+(z*kv_head_num+yin)*head_dim*4;\n" +" const int z4=z << 2;\n" +" float4 Vscale=(float4)scale;\n" +"#ifdef OPENCL_PREFILL_ATTENTION\n" +" __global const FLOAT *B_offset=input1+(z*kv_head_num+yin)*head_dim*4;\n" +" const int x4=x << 2;\n" +" const int query_seq_len4=(query_seq_len+3)/4;\n" +" const int output_offset=y*query_seq_len4*key_seq_len*4;\n" +" float4 out0=0;\n" +" float4 out1=0;\n" +" float4 out2=0;\n" +" float4 out3=0;\n" +" \n" +" const int head_dim4=(head_dim+3)/4;\n" +"#ifdef HEADDIM_LEAVE\n" +" for(int i=0; i= key_seq_len) return;\n" +" vstore4(CONVERT_FLOAT4(out1),0,output+output_offset+x*key_seq_len*4+(z4+1)*4);\n" +" if(z4+2 >= key_seq_len) return;\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+output_offset+x*key_seq_len*4+(z4+2)*4);\n" +" if(z4+3 >= key_seq_len) return;\n" +" vstore4(CONVERT_FLOAT4(out3),0,output+output_offset+x*key_seq_len*4+(z4+3)*4);\n" +"#else\n" +" __global const FLOAT *B_offset=input1+yin*head_dim*4;\n" +" const int key_seq_len4=(key_seq_len+3)/4;\n" +" float4 out=0;\n" +" const int head_dim4=(head_dim+3)/4;\n" +" \n" +"#ifdef HEADDIM_LEAVE\n" +" for(int i=0; i= head_dim) return;\n" +" vstore4(CONVERT_FLOAT4(out1),0,output+x*offset+(y*head_dim+z4+1)*4);\n" +" vstore4(CONVERT_FLOAT4(B.s4567),1,Pastvalue_offset+(value_seq_len4-1)*stride);\n" +" if(z4+2 >= head_dim) return;\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+x*offset+(y*head_dim+z4+2)*4);\n" +" vstore4(CONVERT_FLOAT4(B.s89ab),2,Pastvalue_offset+(value_seq_len4-1)*stride);\n" +" if(z4+3 >= head_dim) return;\n" +" vstore4(CONVERT_FLOAT4(out3),0,output+x*offset+(y*head_dim+z4+3)*4);\n" +" vstore4(CONVERT_FLOAT4(B.scdef),3,Pastvalue_offset+(value_seq_len4-1)*stride);\n" +"#else\n" +" COMPUTE_FLOAT16 B=CONVERT_COMPUTE_FLOAT16(vload16(0,B_offset+(value_seq_len4-1)*stride));\n" +" vstore16(CONVERT_FLOAT16(B),0,Pastvalue_offset+(value_seq_len4-1)*stride);\n" +" COMPUTE_FLOAT *B_ptr=(COMPUTE_FLOAT*)&B;\n" +" for(int i=(value_seq_len4-1)*4,j=0; i> 2)*stride+((value_seq_len-1) % 4);\n" +" \n" +"#ifdef HEADDIM_LEAVE\n" +" Pastvalue_offset[index]=B0;\n" +" output[(y*head_dim+z4)*4]=out.s0;\n" +" if(z4+1 >= head_dim) return;\n" +" Pastvalue_offset[index+4]=B1;\n" +" output[(y*head_dim+z4+1)*4]=out.s1;\n" +" if(z4+2 >= head_dim) return;\n" +" Pastvalue_offset[index+8]=B2;\n" +" output[(y*head_dim+z4+2)*4]=out.s2;\n" +" if(z4+3 >= head_dim) return;\n" +" Pastvalue_offset[index+12]=B3;\n" +" output[(y*head_dim+z4+3)*4]=out.s3;\n" +"#else\n" +" Pastvalue_offset[index]=B0;\n" +" Pastvalue_offset[index+4]=B1;\n" +" Pastvalue_offset[index+8]=B2;\n" +" Pastvalue_offset[index+12]=B3;\n" +" \n" +" output[(y*head_dim+z4)*4]=out.s0;\n" +" output[(y*head_dim+z4+1)*4]=out.s1;\n" +" output[(y*head_dim+z4+2)*4]=out.s2;\n" +" output[(y*head_dim+z4+3)*4]=out.s3;\n" +"#endif\n" +" \n" +"#endif\n" +"}\n" +; #endif #ifndef MNN_OPENCL_BUFFER_CLOSED -{ - "attention_buf", - { 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} - }, +const char* groupnorm_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__kernel void groupnorm_plain_buf(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +"#ifdef DOUBLE_INPUTS\n" +" __global const FLOAT*input0,\n" +" __global const FLOAT*input1,\n" +"#else\n" +" __global const FLOAT*input,\n" +"#endif\n" +" __global FLOAT*output,\n" +" __private const int area,\n" +" __private const int group,\n" +" __private const int inside,\n" +" __private const int outside,\n" +"#ifdef GAMMA_BETA\n" +" __global const FLOAT *gamma,\n" +" __global const FLOAT *beta,\n" +"#endif\n" +" __private float epsilon){\n" +" int3 pos=(int3)(get_global_id(0),get_global_id(1),get_global_id(2));\n" +" float local sum[LOCAL_SIZE];\n" +" if (pos.x> 2;\n" +" \n" +"#ifdef DOUBLE_INPUTS\n" +" // The product of W and H is a multiple of 4\n" +" #ifdef WH_4\n" +" float4 in_sum=0;\n" +" int index=lid;\n" +" for(; index0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid1) {\n" +" sum[lid]=sum[lid]+in_left.y;\n" +" }\n" +" if(inside_remain>2) {\n" +" sum[lid]=sum[lid]+in_left.z;\n" +" }\n" +" if(inside_remain>3) {\n" +" sum[lid]=sum[lid]+in_left.w;\n" +" }\n" +" }\n" +" \n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (lid1) {\n" +" sum[lid]=sum[lid]+in_sum.y;\n" +" }\n" +" if(inside_remain>2) {\n" +" sum[lid]=sum[lid]+in_sum.z;\n" +" }\n" +" if(inside_remain>3) {\n" +" sum[lid]=sum[lid]+in_sum.w;\n" +" }\n" +" }\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (lid= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"inline float4 gelu(float4 in){\n" +" float4 value=0.79788458f*(0.044715f*in*in*in+in);\n" +" float4 x2=value*value;\n" +" float4 dst=value>(float4)5.0f ? (float4)1.0f : (value <= -(float4)5.0f ? -(float4)1.0f :\n" +" (value*(135135.0f+x2*(17325.0f+x2*(378.0f+x2))))/(135135.0f+x2*(62370.0f+x2*(3150.0f+x2*28.0f))));\n" +" return (1.0f+dst)*in*0.5f;\n" +"}\n" +"__kernel void unary_buf_c4_c4(GLOBAL_SIZE_3_DIMS\n" +" __global const INPUT_TYPE *input,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel,\n" +" __private const int input_pad_left,__private const int input_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" const int channel_block_idx=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int hb=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(channel_block_idx,w,hb);\n" +" const int batch_idx=hb/height;\n" +" const int height_idx=hb % height;\n" +" const int channel4=(channel+3)/4;\n" +" const int offset=(((batch_idx*channel4+channel_block_idx)*height+height_idx)*width+w)*4;\n" +" float4 in=convert_float4(vload4(0,input+offset));\n" +" float4 out=OPERATOR;\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+offset);\n" +"}\n" +"__kernel void unary_buf_c4_c16(GLOBAL_SIZE_3_DIMS\n" +" __global const INPUT_TYPE *input,\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel,\n" +" __private const int input_pad_left,__private const int input_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right) {\n" +" const int channel_block_idx=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int hb=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(channel_block_idx,w,hb);\n" +" const int batch_idx=hb/height;\n" +" const int height_idx=hb % height;\n" +" const int dst_width=output_pad_left+width+output_pad_right;\n" +" const int channel4=(channel+3)/4;\n" +" const int channel16=(channel+15)/16;\n" +" const int channe_out_idx=channel_block_idx >> 2;\n" +" const int offset=(((batch_idx*channel4+channel_block_idx)*height+height_idx)*width+w)*4;\n" +" const int dst_offset=(((batch_idx*channel16+channe_out_idx)*height+height_idx)*dst_width+w+output_pad_left)*16+(channel_block_idx % 4)*4;\n" +" float4 in=convert_float4(vload4(0,input+offset));\n" +" float4 out=OPERATOR;\n" +" vstore4(CONVERT_OUTPUT4(out),0,output+dst_offset);\n" +" if(w == 0){\n" +" int pad_offset=(((batch_idx*channel16+channe_out_idx)*height+height_idx)*dst_width)*16+(channel_block_idx % 4)*4;\n" +" for(int i=0; iwidth) {\n" +" for (int i=0; iwidth ? (width % 4) : 4;\n" +" for (int i=0; i= global_size_dim0 || index1 >= global_size_dim1) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void gemm(__read_only image2d_t uInput,__read_only image2d_t uKernel,__write_only image2d_t uOutput,\n" +" __private const int width,__private const int height,__private const int multiLength,__private const int alpha2) {\n" +" \n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1)); \n" +" if (pos.x= 4){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" WI_F(uOutput,(int2)(out_x_idx+3,out_y_idx),o3);\n" +" }else if(remain == 3){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" }else if(remain == 2){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" }else if(remain == 1){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" }\n" +" }\n" +"}\n" +"__kernel void gemmWinogradW2(__read_only image2d_t uInput,__read_only image2d_t uKernel,__write_only image2d_t uOutput,\n" +" __private const int unitWidth,__private const int unitHeight,__private const int dstChannelC4,__private const int multiLength,__private const int alpha2) {\n" +" \n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" const int unitWidth8=(unitWidth+7)/8;\n" +" if (pos.x= 8){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" WI_F(uOutput,(int2)(out_x_idx+3,out_y_idx),o3);\n" +" WI_F(uOutput,(int2)(out_x_idx+4,out_y_idx),o4);\n" +" WI_F(uOutput,(int2)(out_x_idx+5,out_y_idx),o5);\n" +" WI_F(uOutput,(int2)(out_x_idx+6,out_y_idx),o6);\n" +" WI_F(uOutput,(int2)(out_x_idx+7,out_y_idx),o7);\n" +" }else if(remain == 7){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" WI_F(uOutput,(int2)(out_x_idx+3,out_y_idx),o3);\n" +" WI_F(uOutput,(int2)(out_x_idx+4,out_y_idx),o4);\n" +" WI_F(uOutput,(int2)(out_x_idx+5,out_y_idx),o5);\n" +" WI_F(uOutput,(int2)(out_x_idx+6,out_y_idx),o6);\n" +" }else if(remain == 6){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" WI_F(uOutput,(int2)(out_x_idx+3,out_y_idx),o3);\n" +" WI_F(uOutput,(int2)(out_x_idx+4,out_y_idx),o4);\n" +" WI_F(uOutput,(int2)(out_x_idx+5,out_y_idx),o5);\n" +" }else if(remain == 5){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" WI_F(uOutput,(int2)(out_x_idx+3,out_y_idx),o3);\n" +" WI_F(uOutput,(int2)(out_x_idx+4,out_y_idx),o4);\n" +" }else if(remain == 4){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" WI_F(uOutput,(int2)(out_x_idx+3,out_y_idx),o3);\n" +" }else if(remain == 3){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" WI_F(uOutput,(int2)(out_x_idx+2,out_y_idx),o2);\n" +" }else if(remain == 2){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" WI_F(uOutput,(int2)(out_x_idx+1,out_y_idx),o1);\n" +" }else if(remain == 1){\n" +" WI_F(uOutput,(int2)(out_x_idx,out_y_idx),o0);\n" +" }\n" +" }\n" +"}\n" +"#ifdef INPUT_CHANNEL_LEAVE\n" +" #define PADZEROSVEC(k, channel, data0, data1, data2, data3) "" data0 = (k << 2) < channel ? data0 : 0; "" data1 = (k << 2) + 1 < channel ? data1 : 0; "" data2 = (k << 2) + 2 < channel ? data2 : 0; "" data3=(k << 2)+3> 4)-8;\n" +" charWeights.s1=(charWeightsInt4.s0 & 15)-8;\n" +" charWeights.s2=(charWeightsInt4.s1 >> 4)-8;\n" +" charWeights.s3=(charWeightsInt4.s1 & 15)-8;\n" +" charWeights.s4=(charWeightsInt4.s2 >> 4)-8;\n" +" charWeights.s5=(charWeightsInt4.s2 & 15)-8;\n" +" charWeights.s6=(charWeightsInt4.s3 >> 4)-8;\n" +" charWeights.s7=(charWeightsInt4.s3 & 15)-8;\n" +" charWeights.s8=(charWeightsInt4.s4 >> 4)-8;\n" +" charWeights.s9=(charWeightsInt4.s4 & 15)-8;\n" +" charWeights.sa=(charWeightsInt4.s5 >> 4)-8;\n" +" charWeights.sb=(charWeightsInt4.s5 & 15)-8;\n" +" charWeights.sc=(charWeightsInt4.s6 >> 4)-8;\n" +" charWeights.sd=(charWeightsInt4.s6 & 15)-8;\n" +" charWeights.se=(charWeightsInt4.s7 >> 4)-8;\n" +" charWeights.sf=(charWeightsInt4.s7 & 15)-8;\n" +" FLOAT16 weights=CONVERT_FLOAT16(charWeights)*scale+offset;\n" +" \n" +"#else\n" +" FLOAT16 weights=vload16(0,weight+weight_offset+k*weight_oc_offset);\n" +"#endif\n" +" PADZEROSVEC(k,srcChannel,weights.s0123,weights.s4567,weights.s89ab,weights.scdef);\n" +" \n" +" out=mad((FLOAT4)in.x,(FLOAT4)weights.s0123,out);\n" +" out=mad((FLOAT4)in.y,(FLOAT4)weights.s4567,out);\n" +" out=mad((FLOAT4)in.z,(FLOAT4)weights.s89ab,out);\n" +" out=mad((FLOAT4)in.w,(FLOAT4)weights.scdef,out);\n" +" }\n" +" \n" +"#ifdef RELU\n" +" out=fmax(out,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out=clamp(out,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" WI_F(output,(int2)(pos.x,pos.y),out);\n" +"}\n" +"__kernel void gemm_conv_b2(GLOBAL_SIZE_DIM2\n" +" __read_only image2d_t input,\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" __global const char *weight,\n" +" __global const float *dequantScaleOffset,\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" __global const uchar *weight,\n" +" __global const float *dequantScaleOffset,\n" +"#else\n" +" __global const FLOAT *weight,\n" +"#endif\n" +" __read_only image2d_t bias,\n" +" __write_only image2d_t output,\n" +" __private const int dstChannelC4,\n" +" __private const int srcChannelC4,\n" +" __private const int batch\n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8) || (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" ,__private const int blockDim\n" +" ,__private const int srcChannel\n" +"#endif\n" +") {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1)); //cout/4,b\n" +" UNIFORM_BOUNDRY_CHECK(pos.x,pos.y);\n" +" int pos_x=pos.x << 2;\n" +" int pos_y=pos.y << 1;\n" +" FLOAT4 bias0=RI_F(bias,SAMPLER,(int2)(pos.x,0));\n" +" FLOAT4 out0=bias0,out1=bias0;\n" +" \n" +"#if (defined USE_LOW_BIT_WEIGHT_INT8)\n" +" int weight_offset=pos.x*16;\n" +" int weight_oc_offset=dstChannelC4*16;\n" +"#elif (defined USE_LOW_BIT_WEIGHT_INT4)\n" +" int weight_offset=pos.x*8;\n" +" int weight_oc_offset=dstChannelC4*8;\n" +"#else\n" +" int weight_offset=pos.x*16;\n" +" int weight_oc_offset=dstChannelC4*16;\n" +"#endif\n" +" for (int k=0; k> 4)-8;\n" +" charWeights.s1=(charWeightsInt4.s0 & 15)-8;\n" +" charWeights.s2=(charWeightsInt4.s1 >> 4)-8;\n" +" charWeights.s3=(charWeightsInt4.s1 & 15)-8;\n" +" charWeights.s4=(charWeightsInt4.s2 >> 4)-8;\n" +" charWeights.s5=(charWeightsInt4.s2 & 15)-8;\n" +" charWeights.s6=(charWeightsInt4.s3 >> 4)-8;\n" +" charWeights.s7=(charWeightsInt4.s3 & 15)-8;\n" +" charWeights.s8=(charWeightsInt4.s4 >> 4)-8;\n" +" charWeights.s9=(charWeightsInt4.s4 & 15)-8;\n" +" charWeights.sa=(charWeightsInt4.s5 >> 4)-8;\n" +" charWeights.sb=(charWeightsInt4.s5 & 15)-8;\n" +" charWeights.sc=(charWeightsInt4.s6 >> 4)-8;\n" +" charWeights.sd=(charWeightsInt4.s6 & 15)-8;\n" +" charWeights.se=(charWeightsInt4.s7 >> 4)-8;\n" +" charWeights.sf=(charWeightsInt4.s7 & 15)-8;\n" +" FLOAT16 weights=CONVERT_FLOAT16(charWeights)*scale+offset;\n" +"#else\n" +" FLOAT16 weights=vload16(0,weight+weight_offset+k*weight_oc_offset);\n" +"#endif\n" +" PADZEROSVEC(k,srcChannel,weights.s0123,weights.s4567,weights.s89ab,weights.scdef);\n" +" \n" +" out0=mad((FLOAT4)in0.x,(FLOAT4)weights.s0123,out0);\n" +" out0=mad((FLOAT4)in0.y,(FLOAT4)weights.s4567,out0);\n" +" out0=mad((FLOAT4)in0.z,(FLOAT4)weights.s89ab,out0);\n" +" out0=mad((FLOAT4)in0.w,(FLOAT4)weights.scdef,out0);\n" +" \n" +" out1=mad((FLOAT4)in1.x,(FLOAT4)weights.s0123,out1);\n" +" out1=mad((FLOAT4)in1.y,(FLOAT4)weights.s4567,out1);\n" +" out1=mad((FLOAT4)in1.z,(FLOAT4)weights.s89ab,out1);\n" +" out1=mad((FLOAT4)in1.w,(FLOAT4)weights.scdef,out1);\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(FLOAT4)0);\n" +" out1=fmax(out1,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(FLOAT4)0,(FLOAT4)6);\n" +" out1=clamp(out1,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" WI_F(output,(int2)(pos.x,pos_y),out0);\n" +" if(pos_y+1= input_shape.y)); "" in##i=read_imagef(input,SAMPLER,(int2)(in_width_value##i,in_hb_value));\n" +"#define CALCULATE_OUTPUT(i) "" out##i = mad(in##i.x, weights0, out##i); "" out##i = mad(in##i.y, weights1, out##i); "" out##i = mad(in##i.z, weights2, out##i); "" out##i=mad(in##i.w,weights3,out##i);\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void depthwise_deconv2d(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,\n" +" __read_only image2d_t weights,\n" +" #ifndef NO_BIAS\n" +" __read_only image2d_t bias,\n" +" #endif\n" +" __write_only image2d_t output,\n" +" __private const int2 input_shape,\n" +" __private const int2 output_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 align_shape,\n" +" __private const int2 padding_shape,\n" +" __private const int2 kernel_shape,\n" +" __private const int kernel_size,__private const int out_channel_blocks) {\n" +" const int out_channel_blocks_idx=get_global_id(0);\n" +" const int out_width_idx=get_global_id(1);\n" +" const int out_batch_height_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(out_channel_blocks_idx,out_width_idx,out_batch_height_idx);\n" +" #ifndef NO_BIAS\n" +" float4 out0=read_imagef(bias,SAMPLER,(int2)(out_channel_blocks_idx,0));\n" +" #else\n" +" float4 out0=(float4)(0.0);\n" +" #endif\n" +" const int out_batch_idx=out_batch_height_idx/output_shape.x;\n" +" const int out_height_idx=out_batch_height_idx % output_shape.x;\n" +" int kernel_start_x=(out_width_idx+align_shape.y)/stride_shape.y;\n" +" int kernel_start_y=(out_height_idx+align_shape.x)/stride_shape.x;\n" +" int deal_kernel_width=kernel_shape.y-mad24(kernel_start_x,stride_shape.y,padding_shape.y)+out_width_idx-1;\n" +" int deal_kernel_height=kernel_shape.x-mad24(kernel_start_y,stride_shape.x,padding_shape.x)+out_height_idx-1;\n" +" int kernel_image_x;\n" +" float4 in0;\n" +" float4 weight;\n" +" int in_width0;\n" +" int in_idx,in_idy;\n" +" for (int k_y=deal_kernel_height,idx_h=kernel_start_y; k_y >= 0; k_y -= stride_shape.x,idx_h++) {\n" +" in_idy=mad24(out_batch_idx,input_shape.x,idx_h);\n" +" int in_hb_value=select(in_idy,-1,idx_h<0 || idx_h >= input_shape.x);\n" +" for (int k_x=deal_kernel_width,in_width_idx=kernel_start_x; k_x >= 0; k_x -= stride_shape.y,in_width_idx++) {\n" +" in_width0=in_width_idx;\n" +" in_idx=mul24(out_channel_blocks_idx,input_shape.y);\n" +" READ_INPUT_IMAGE(0,0);\n" +" kernel_image_x=mad24(k_y,kernel_shape.y,k_x);\n" +" weight=read_imagef(weights,SAMPLER,(int2)(kernel_image_x,out_channel_blocks_idx));\n" +" out0=mad(in0,weight,out0);\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(float4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(float4)0,(float4)6);\n" +"#endif\n" +" const int output_image_x=mad24(out_channel_blocks_idx,output_shape.y,out_width_idx);\n" +" write_imagef(output,(int2)(output_image_x,out_batch_height_idx),out0);\n" +" }\n" +"}\n" +; +const char* range = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void range(GLOBAL_SIZE_3_DIMS\n" +" __read_only image2d_t input0,\n" +" __read_only image2d_t input2,\n" +" __write_only image2d_t output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel,\n" +" __private const int channelBlock\n" +" ) {\n" +" const int width_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/channelBlock;\n" +" const int channel_idx=batch_channel_idx % channelBlock;\n" +" \n" +" const int bh=batch_idx*height+height_idx;\n" +" const int cw=channel_idx*width+width_idx;\n" +" const int channel4=channel_idx << 2;\n" +" int index=(((batch_idx*channel)+channel4)*height+height_idx)*width+width_idx;\n" +" int size=height*width;\n" +" int4 index4=(int4)(index,index+size,index+size*2,index+size*3);\n" +" INPUT_TYPE_I start=RI_DATA(input0,SAMPLER,(int2)(0,0)).x;\n" +" INPUT_TYPE_I step=RI_DATA(input2,SAMPLER,(int2)(0,0)).x;\n" +" OUTPUT_TYPE_I4 value=(OUTPUT_TYPE_I4)start+CONVERT_OUTPUT_I4(index4)*(OUTPUT_TYPE_I4)step;\n" +" WI_DATA(output,(int2)(cw,bh),value);\n" +"}\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* scale_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__kernel void scale_buf(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT* input,\n" +" __global const FLOAT* scale,\n" +"#ifdef BIAS\n" +" __global const FLOAT* bias,\n" +"#endif\n" +" __global FLOAT* output,\n" +" __private const int4 shape) {//N,H,W,C4\n" +" const int out_w_c_idx=get_global_id(0);\n" +" const int out_h_b_idx=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(out_w_c_idx,out_h_b_idx);\n" +" const int out_b_idx=out_h_b_idx/shape.y;\n" +" const int out_h_idx=out_h_b_idx % shape.y;\n" +" const int out_c_idx=out_w_c_idx/shape.z;\n" +" const int out_w_idx=out_w_c_idx % shape.z;\n" +" \n" +" const int offset=(((out_b_idx*shape.w+out_c_idx)*shape.y+out_h_idx)*shape.z+out_w_idx)*4;\n" +" COMPUTE_FLOAT4 in_value=CONVERT_COMPUTE_FLOAT4(vload4(0,input+offset));\n" +" COMPUTE_FLOAT4 scale_value=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,scale));\n" +"#ifdef BIAS\n" +" COMPUTE_FLOAT4 bias_value=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out_value=in_value*scale_value+bias_value;\n" +"#else\n" +" COMPUTE_FLOAT4 out_value=in_value*scale_value;\n" +"#endif\n" +" vstore4(CONVERT_FLOAT4(out_value),0,output+offset);\n" +"}\n" +; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* matmul_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) ""if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { ""return; ""}\n" +"__kernel void matmul_buf(GLOBAL_SIZE_2_DIMS __global const FLOAT* input_a,\n" +" __global const FLOAT* input_b,\n" +" #ifdef BIAS\n" +" __global const FLOAT* input_c,\n" +" #endif\n" +" __global FLOAT* output_c,\n" +" __private const int channels,\n" +" __private const int channel_blocks,\n" +" __private const int width_blocks,\n" +" __private const int width) {\n" +" const int width_blocks_idx=get_global_id(0);// output W\n" +" const int height_idx=get_global_id(1);// output H\n" +" DEAL_NON_UNIFORM_DIM2(width_blocks_idx,height_idx);\n" +" COMPUTE_FLOAT4 a;\n" +" COMPUTE_FLOAT4 b0=0,b1=0,b2=0,b3=0;\n" +" COMPUTE_FLOAT4 v_zero=(COMPUTE_FLOAT4)((COMPUTE_FLOAT)0.0);\n" +" #ifdef BIAS\n" +" COMPUTE_FLOAT4 temp=CONVERT_COMPUTE_FLOAT4(vload4(width_blocks_idx,input_c));\n" +" COMPUTE_FLOAT result0=temp.x;\n" +" COMPUTE_FLOAT result1=temp.y;\n" +" COMPUTE_FLOAT result2=temp.z;\n" +" COMPUTE_FLOAT result3=temp.w;\n" +" #else\n" +" COMPUTE_FLOAT result0=0;\n" +" COMPUTE_FLOAT result1=0;\n" +" COMPUTE_FLOAT result2=0;\n" +" COMPUTE_FLOAT result3=0;\n" +" #endif\n" +" const int remain=channel_blocks*4-channels;\n" +" for (short pos=0; pos= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+width_blocks,input_b));\n" +" b2=(remain >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+width_blocks*2,input_b));\n" +" b3=(remain >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+width_blocks*3,input_b));\n" +" if (remain == 3) {\n" +" a.y=0;\n" +" a.z=0;\n" +" a.w=0;\n" +" } else if (remain == 2) {\n" +" a.z=0;\n" +" a.w=0;\n" +" } else if (remain == 1) {\n" +" a.w=0;;\n" +" }\n" +" COMPUTE_FLOAT4 btmp0=(COMPUTE_FLOAT4)(b0.s0,b1.s0,b2.s0,b3.s0);\n" +" COMPUTE_FLOAT4 btmp1=(COMPUTE_FLOAT4)(b0.s1,b1.s1,b2.s1,b3.s1);\n" +" COMPUTE_FLOAT4 btmp2=(COMPUTE_FLOAT4)(b0.s2,b1.s2,b2.s2,b3.s2);\n" +" COMPUTE_FLOAT4 btmp3=(COMPUTE_FLOAT4)(b0.s3,b1.s3,b2.s3,b3.s3);\n" +" result0 += dot(a,btmp0);\n" +" result1 += dot(a,btmp1);\n" +" result2 += dot(a,btmp2);\n" +" result3 += dot(a,btmp3);\n" +" }\n" +" const int out_offset=height_idx*width_blocks+width_blocks_idx;\n" +" vstore4(CONVERT_FLOAT4((COMPUTE_FLOAT4)(result0,result1,result2,result3)),out_offset,output_c);\n" +"}\n" +"__kernel void matmul_transB_buf(GLOBAL_SIZE_2_DIMS __global const FLOAT* input_a,\n" +" __global const FLOAT* input_b,\n" +" #ifdef BIAS\n" +" __global const FLOAT* input_c,\n" +" #endif\n" +" __global FLOAT* output_c,\n" +" __private const int channels,\n" +" __private const int channel_blocks,\n" +" __private const int width_blocks,\n" +" __private const int width) {\n" +" const int width_blocks_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(width_blocks_idx,height_idx);\n" +" COMPUTE_FLOAT4 a;\n" +" COMPUTE_FLOAT4 b0=0,b1=0,b2=0,b3=0;\n" +" COMPUTE_FLOAT4 v_zero=(COMPUTE_FLOAT4)((COMPUTE_FLOAT)0.0);\n" +" #ifdef BIAS\n" +" COMPUTE_FLOAT4 temp=CONVERT_COMPUTE_FLOAT4(vload4(width_blocks_idx,input_c));\n" +" COMPUTE_FLOAT result0=temp.x;\n" +" COMPUTE_FLOAT result1=temp.y;\n" +" COMPUTE_FLOAT result2=temp.z;\n" +" COMPUTE_FLOAT result3=temp.w;\n" +" #else\n" +" COMPUTE_FLOAT result0=0;\n" +" COMPUTE_FLOAT result1=0;\n" +" COMPUTE_FLOAT result2=0;\n" +" COMPUTE_FLOAT result3=0;\n" +" #endif\n" +" const int remaina=channel_blocks*4-channels;\n" +" const int remainb=(width_blocks_idx+1)*4-width;\n" +" for (short pos=0; pos= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks,input_b));\n" +" b2=(remainb >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*2,input_b));\n" +" b3=(remainb >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*3,input_b));\n" +" result0 += dot(a,b0);\n" +" result1 += dot(a,b1);\n" +" result2 += dot(a,b2);\n" +" result3 += dot(a,b3);\n" +" }\n" +" \n" +" {\n" +" const int inpa_offset=height_idx*channel_blocks+channel_blocks-1;\n" +" a=CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset,input_a));\n" +" const int inpb_offset=(width_blocks_idx*4)*channel_blocks+channel_blocks-1;\n" +" b0=CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset,input_b));\n" +" b1=(remainb >= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks,input_b));\n" +" b2=(remainb >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*2,input_b));\n" +" b3=(remainb >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*3,input_b));\n" +" if (remaina == 3) {\n" +" a.y=0;\n" +" a.z=0;\n" +" a.w=0;\n" +" } else if (remaina == 2) {\n" +" a.z=0;\n" +" a.w=0;\n" +" } else if (remaina == 1) {\n" +" a.w=0;\n" +" }\n" +" result0 += dot(a,b0);\n" +" result1 += dot(a,b1);\n" +" result2 += dot(a,b2);\n" +" result3 += dot(a,b3);\n" +" }\n" +" const int out_offset=height_idx*width_blocks+width_blocks_idx;\n" +" vstore4(CONVERT_FLOAT4((COMPUTE_FLOAT4)(result0,result1,result2,result3)),out_offset,output_c);\n" +"}\n" +"__kernel void matmul_transA_buf(GLOBAL_SIZE_2_DIMS __global const FLOAT* input_a,\n" +" __global const FLOAT* input_b,\n" +" #ifdef BIAS\n" +" __global const FLOAT* input_c,\n" +" #endif\n" +" __global FLOAT* output_c,\n" +" __private const int channels,\n" +" __private const int channel_blocks,\n" +" __private const int height,\n" +" __private const int height_blocks,\n" +" __private const int width_blocks,\n" +" __private const int width) {\n" +" const int width_blocks_idx=get_global_id(0);\n" +" const int height_blocks_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(width_blocks_idx,height_blocks_idx);\n" +" COMPUTE_FLOAT4 v_zero=(COMPUTE_FLOAT4)((COMPUTE_FLOAT)0.0);\n" +" #ifdef BIAS\n" +" COMPUTE_FLOAT4 result0=CONVERT_COMPUTE_FLOAT4(vload4(width_blocks_idx,input_c));\n" +" COMPUTE_FLOAT4 result1=result0;\n" +" COMPUTE_FLOAT4 result2=result0;\n" +" COMPUTE_FLOAT4 result3=result0;\n" +" #else\n" +" COMPUTE_FLOAT4 result0=0;\n" +" COMPUTE_FLOAT4 result1=0;\n" +" COMPUTE_FLOAT4 result2=0;\n" +" COMPUTE_FLOAT4 result3=0;\n" +" #endif\n" +" \n" +" const int remain=channel_blocks*4-channels;\n" +" for (short pos=0; pos= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset+height_blocks,input_a)));\n" +" COMPUTE_FLOAT4 a2=((remain >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset+height_blocks*2,input_a)));\n" +" COMPUTE_FLOAT4 a3=((remain >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset+height_blocks*3,input_a)));\n" +" const int inpb_offset=(4*(channel_blocks-1))*width_blocks+width_blocks_idx;\n" +" COMPUTE_FLOAT4 b0=CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset,input_b));\n" +" COMPUTE_FLOAT4 b1=((remain >= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+width_blocks,input_b)));\n" +" COMPUTE_FLOAT4 b2=((remain >= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+width_blocks*2,input_b)));\n" +" COMPUTE_FLOAT4 b3=((remain >= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+width_blocks*3,input_b)));\n" +" COMPUTE_FLOAT4 a0_trans=(COMPUTE_FLOAT4)(a0.x,a1.x,a2.x,a3.x);\n" +" COMPUTE_FLOAT4 a1_trans=(COMPUTE_FLOAT4)(a0.y,a1.y,a2.y,a3.y);\n" +" COMPUTE_FLOAT4 a2_trans=(COMPUTE_FLOAT4)(a0.z,a1.z,a2.z,a3.z);\n" +" COMPUTE_FLOAT4 a3_trans=(COMPUTE_FLOAT4)(a0.w,a1.w,a2.w,a3.w);\n" +" \n" +" COMPUTE_FLOAT4 b0_trans=(COMPUTE_FLOAT4)(b0.x,b1.x,b2.x,b3.x);\n" +" COMPUTE_FLOAT4 b1_trans=(COMPUTE_FLOAT4)(b0.y,b1.y,b2.y,b3.y);\n" +" COMPUTE_FLOAT4 b2_trans=(COMPUTE_FLOAT4)(b0.z,b1.z,b2.z,b3.z);\n" +" COMPUTE_FLOAT4 b3_trans=(COMPUTE_FLOAT4)(b0.w,b1.w,b2.w,b3.w);\n" +" //matmul\n" +" result0.x += dot(a0_trans,b0_trans);\n" +" result0.y += dot(a0_trans,b1_trans);\n" +" result0.z += dot(a0_trans,b2_trans);\n" +" result0.w += dot(a0_trans,b3_trans);\n" +" \n" +" result1.x += dot(a1_trans,b0_trans);\n" +" result1.y += dot(a1_trans,b1_trans);\n" +" result1.z += dot(a1_trans,b2_trans);\n" +" result1.w += dot(a1_trans,b3_trans);\n" +" \n" +" result2.x += dot(a2_trans,b0_trans);\n" +" result2.y += dot(a2_trans,b1_trans);\n" +" result2.z += dot(a2_trans,b2_trans);\n" +" result2.w += dot(a2_trans,b3_trans);\n" +" \n" +" result3.x += dot(a3_trans,b0_trans);\n" +" result3.y += dot(a3_trans,b1_trans);\n" +" result3.z += dot(a3_trans,b2_trans);\n" +" result3.w += dot(a3_trans,b3_trans);\n" +" }\n" +" \n" +" const int out_offset=(4*height_blocks_idx)*width_blocks+width_blocks_idx;\n" +" vstore4(CONVERT_FLOAT4(result0),out_offset,output_c);\n" +" if(4*height_blocks_idx+1 >= height) return;\n" +" vstore4(CONVERT_FLOAT4(result1),out_offset+width_blocks,output_c);\n" +" if(4*height_blocks_idx+2 >= height) return;\n" +" vstore4(CONVERT_FLOAT4(result2),out_offset+width_blocks*2,output_c);\n" +" if(4*height_blocks_idx+3 >= height) return;\n" +" vstore4(CONVERT_FLOAT4(result3),out_offset+width_blocks*3,output_c);\n" +"}\n" +"__kernel void matmul_transA_transB_buf(GLOBAL_SIZE_2_DIMS __global const FLOAT* input_a,\n" +" __global const FLOAT* input_b,\n" +" #ifdef BIAS\n" +" __global const FLOAT* input_c,\n" +" #endif\n" +" __global FLOAT* output_c,\n" +" __private const int channels,\n" +" __private const int channel_blocks,\n" +" __private const int height,\n" +" __private const int height_blocks,\n" +" __private const int width_blocks,\n" +" __private const int width) {\n" +" const int width_blocks_idx=get_global_id(0);\n" +" const int height_blocks_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(width_blocks_idx,height_blocks_idx);\n" +" COMPUTE_FLOAT4 v_zero=(COMPUTE_FLOAT4)((COMPUTE_FLOAT)0.0);\n" +" #ifdef BIAS\n" +" COMPUTE_FLOAT4 result0=CONVERT_COMPUTE_FLOAT4(vload4(width_blocks_idx,input_c));\n" +" COMPUTE_FLOAT4 result1=result0;\n" +" COMPUTE_FLOAT4 result2=result0;\n" +" COMPUTE_FLOAT4 result3=result0;\n" +" #else\n" +" COMPUTE_FLOAT4 result0=0;\n" +" COMPUTE_FLOAT4 result1=0;\n" +" COMPUTE_FLOAT4 result2=0;\n" +" COMPUTE_FLOAT4 result3=0;\n" +" #endif\n" +" \n" +" const int remaina=channel_blocks*4-channels;\n" +" const int remainb=(width_blocks_idx+1)*4-width;\n" +" for (short pos=0; pos= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks,input_b)));\n" +" COMPUTE_FLOAT4 b2=((remainb >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*2,input_b)));\n" +" COMPUTE_FLOAT4 b3=((remainb >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*3,input_b)));\n" +" COMPUTE_FLOAT4 a0_trans=(COMPUTE_FLOAT4)(a0.x,a1.x,a2.x,a3.x);\n" +" COMPUTE_FLOAT4 a1_trans=(COMPUTE_FLOAT4)(a0.y,a1.y,a2.y,a3.y);\n" +" COMPUTE_FLOAT4 a2_trans=(COMPUTE_FLOAT4)(a0.z,a1.z,a2.z,a3.z);\n" +" COMPUTE_FLOAT4 a3_trans=(COMPUTE_FLOAT4)(a0.w,a1.w,a2.w,a3.w);\n" +" //matmul\n" +" result0.x += dot(a0_trans,b0);\n" +" result0.y += dot(a0_trans,b1);\n" +" result0.z += dot(a0_trans,b2);\n" +" result0.w += dot(a0_trans,b3);\n" +" \n" +" result1.x += dot(a1_trans,b0);\n" +" result1.y += dot(a1_trans,b1);\n" +" result1.z += dot(a1_trans,b2);\n" +" result1.w += dot(a1_trans,b3);\n" +" \n" +" result2.x += dot(a2_trans,b0);\n" +" result2.y += dot(a2_trans,b1);\n" +" result2.z += dot(a2_trans,b2);\n" +" result2.w += dot(a2_trans,b3);\n" +" \n" +" result3.x += dot(a3_trans,b0);\n" +" result3.y += dot(a3_trans,b1);\n" +" result3.z += dot(a3_trans,b2);\n" +" result3.w += dot(a3_trans,b3);\n" +" }\n" +" \n" +" {\n" +" const int inpa_offset=(4*(channel_blocks-1))*height_blocks+height_blocks_idx;\n" +" COMPUTE_FLOAT4 a0=CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset,input_a));\n" +" COMPUTE_FLOAT4 a1=((remaina >= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset+height_blocks,input_a)));\n" +" COMPUTE_FLOAT4 a2=((remaina >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset+height_blocks*2,input_a)));\n" +" COMPUTE_FLOAT4 a3=((remaina >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpa_offset+height_blocks*3,input_a)));\n" +" const int inpb_offset=(4*width_blocks_idx)*channel_blocks+channel_blocks-1;\n" +" COMPUTE_FLOAT4 b0=CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset,input_b));\n" +" COMPUTE_FLOAT4 b1=((remainb >= 3) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks,input_b)));\n" +" COMPUTE_FLOAT4 b2=((remainb >= 2) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*2,input_b)));\n" +" COMPUTE_FLOAT4 b3=((remainb >= 1) ? v_zero : CONVERT_COMPUTE_FLOAT4(vload4(inpb_offset+channel_blocks*3,input_b)));\n" +" COMPUTE_FLOAT4 a0_trans=(COMPUTE_FLOAT4)(a0.x,a1.x,a2.x,a3.x);\n" +" COMPUTE_FLOAT4 a1_trans=(COMPUTE_FLOAT4)(a0.y,a1.y,a2.y,a3.y);\n" +" COMPUTE_FLOAT4 a2_trans=(COMPUTE_FLOAT4)(a0.z,a1.z,a2.z,a3.z);\n" +" COMPUTE_FLOAT4 a3_trans=(COMPUTE_FLOAT4)(a0.w,a1.w,a2.w,a3.w);\n" +" //matmul\n" +" result0.x += dot(a0_trans,b0);\n" +" result0.y += dot(a0_trans,b1);\n" +" result0.z += dot(a0_trans,b2);\n" +" result0.w += dot(a0_trans,b3);\n" +" \n" +" result1.x += dot(a1_trans,b0);\n" +" result1.y += dot(a1_trans,b1);\n" +" result1.z += dot(a1_trans,b2);\n" +" result1.w += dot(a1_trans,b3);\n" +" \n" +" result2.x += dot(a2_trans,b0);\n" +" result2.y += dot(a2_trans,b1);\n" +" result2.z += dot(a2_trans,b2);\n" +" result2.w += dot(a2_trans,b3);\n" +" \n" +" result3.x += dot(a3_trans,b0);\n" +" result3.y += dot(a3_trans,b1);\n" +" result3.z += dot(a3_trans,b2);\n" +" result3.w += dot(a3_trans,b3);\n" +" }\n" +" const int out_offset=(4*height_blocks_idx)*width_blocks+width_blocks_idx;\n" +" vstore4(CONVERT_FLOAT4(result0),out_offset,output_c);\n" +" if(4*height_blocks_idx+1 >= height) return;\n" +" vstore4(CONVERT_FLOAT4(result1),out_offset+width_blocks,output_c);\n" +" if(4*height_blocks_idx+2 >= height) return;\n" +" vstore4(CONVERT_FLOAT4(result2),out_offset+width_blocks*2,output_c);\n" +" if(4*height_blocks_idx+3 >= height) return;\n" +" vstore4(CONVERT_FLOAT4(result3),out_offset+width_blocks*3,output_c);\n" +"}\n" +; +#endif +const char* pooling = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void pooling(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,\n" +" __private const int2 input_shape,__private const int output_height,__private const int2 pad_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 kernel_shape,\n" +" __write_only image2d_t output,\n" +" __write_only image2d_t rediceOutput) {\n" +" const int output_channel_idx=get_global_id(0);\n" +" const int output_width_idx=get_global_id(1);\n" +" const int output_batch_height_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(output_channel_idx,output_width_idx,output_batch_height_idx);\n" +" const int output_width=global_size_dim1;\n" +" const int output_batch_idx=output_batch_height_idx/output_height;\n" +" const int output_height_idx=output_batch_height_idx-mul24(output_batch_idx,output_height);\n" +" const int input_start=mul24(output_batch_idx,input_shape.x);\n" +" const int input_height_start=mad24(output_height_idx,stride_shape.x,-pad_shape.x);\n" +" const int input_width_start=mad24(output_width_idx,stride_shape.y,-pad_shape.y);\n" +" const int input_channel_start=mul24(output_channel_idx,input_shape.y);\n" +"#ifdef POOL_AVG\n" +" FLOAT4 output_result=0;\n" +" for (int height=0; height= input_shape.x));\n" +" for (int width=0; width= input_shape.y));\n" +" FLOAT4 input_data=RI_F(input,SAMPLER,(int2)(input_width_idx,input_height_idx));\n" +" output_result=output_result+input_data;\n" +" }\n" +" }\n" +" const int kernel_height_start=max(0,input_height_start);\n" +" const int kernel_width_start=max(0,input_width_start);\n" +" const int kernel_height_end=min(input_height_start+kernel_shape.x,input_shape.x);\n" +" const int kernel_width_end=min(input_width_start+kernel_shape.y,input_shape.y);\n" +" #ifdef COUNT_INCLUDE_PADDING\n" +" const int block_size=(min(input_height_start+kernel_shape.x,input_shape.x+pad_shape.x)-input_height_start)*(min(input_width_start+kernel_shape.y,input_shape.y+pad_shape.y)-input_width_start);\n" +" #else\n" +" const int block_size=mul24((kernel_height_end-kernel_height_start),(kernel_width_end-kernel_width_start));\n" +" #endif\n" +" const FLOAT block_float_req=(FLOAT)1.0f/(FLOAT)block_size;\n" +" output_result=output_result*block_float_req;\n" +"#else\n" +" FLOAT4 output_result=(FLOAT4)(-FLT_MAX);\n" +" #if RETURN_REDICE\n" +" int4 redice=(int4)0;\n" +" #endif\n" +" for (int height=0; height= input_shape.x));\n" +" if (input_height_idx != -1) {\n" +" for (int width=0; width= input_shape.y));\n" +" if (input_width_idx != -1) {\n" +" FLOAT4 input_data=RI_F(input,SAMPLER,(int2)(input_width_idx,input_height_idx));\n" +" #if RETURN_REDICE\n" +" redice=input_data>output_result ? (int4)((input_height_start+height)*input_shape.y+input_width_start+width) : redice;\n" +" #endif\n" +" output_result=fmax(output_result,input_data);\n" +" }\n" +" }\n" +" }\n" +" }\n" +"#endif\n" +" const int output_channel_width_idx=mad24(output_channel_idx,output_width,output_width_idx);\n" +" WI_F(output,(int2)(output_channel_width_idx,output_batch_height_idx),output_result);\n" +" #if RETURN_REDICE\n" +" WI_F(rediceOutput,(int2)(output_channel_width_idx,output_batch_height_idx),CONVERT_FLOAT4(redice));\n" +" #endif\n" +"}\n" +"#ifdef LOCAL_SIZE\n" +"__kernel void global_pooling(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,\n" +" __private const int2 input_shape,__private const int output_height,__private const int2 pad_shape,\n" +" __private const int2 stride_shape,\n" +" __private const int2 kernel_shape,\n" +" __write_only image2d_t output,\n" +" __write_only image2d_t rediceOutput) {\n" +" const int local_id=get_local_id(0);\n" +" const int output_channel_idx=get_global_id(1);\n" +" const int output_batch_idx=get_global_id(2);\n" +"#ifdef POOL_AVG\n" +" FLOAT4 output_result=0;\n" +"#else\n" +" FLOAT4 output_result=(FLOAT4)(-FLT_MAX);\n" +"#if RETURN_REDICE\n" +" int4 redice=(int4)0;\n" +" int4 local rediceId[LOCAL_SIZE];\n" +"#endif\n" +"#endif\n" +" FLOAT4 local sum[LOCAL_SIZE];\n" +" int wc=output_channel_idx*input_shape.y;\n" +" int bh=output_batch_idx*input_shape.x;\n" +" for(int i=local_id; ioutput_result ? (int4)(i) : redice;\n" +"#endif\n" +"#endif\n" +" }\n" +" \n" +" sum[local_id]=output_result;\n" +"#if RETURN_REDICE\n" +" rediceId[local_id]=redice;\n" +"#endif\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (local_idsum[local_id+i] ? rediceId[local_id] : rediceId[local_id+i];\n" +"#endif\n" +" }\n" +"#endif\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" }\n" +" output_result=sum[0];\n" +"#ifdef POOL_AVG\n" +" output_result /= (input_shape.x*input_shape.y);\n" +"#endif\n" +" WI_F(output,(int2)(output_channel_idx,output_batch_idx),output_result);\n" +" #if RETURN_REDICE\n" +" redice=rediceId[0];\n" +" WI_F(rediceOutput,(int2)(output_channel_idx,output_batch_idx),CONVERT_FLOAT4(redice));\n" +" #endif\n" +"}\n" +"#endif\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* conv_2d_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__kernel\n" +"void conv_2d_1x1_c4h1w4(GLOBAL_SIZE_2_DIMS __private const int out_w_blocks,\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *kernel_ptr,\n" +" __global const FLOAT *bias_ptr,\n" +" __global FLOAT *output,\n" +" __private const int in_c_block,\n" +" __private const int out_h,\n" +" __private const int out_w,\n" +" __private const int out_c_block) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h; // equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_h; // equal to in_h_idx\n" +" const int out_w4_idx=mul24(out_w_idx,4);\n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias_ptr));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=out0;\n" +" COMPUTE_FLOAT4 out3=out0;\n" +" const int intput_width_idx0=out_w4_idx;\n" +" \n" +" int offset=mul24(out_c_idx,in_c_block) << 2;\n" +" int inp_offset=(((out_b_idx*in_c_block)*out_h+out_h_idx)* out_w+intput_width_idx0) << 2;\n" +" \n" +" const int inp_add=out_h*out_w*4;\n" +" for (ushort in_channel_block_idx=0; in_channel_block_idx= 4) {\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +" } else if (remain == 3) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2,output+out_offset);\n" +" } else if (remain == 2) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_1x1_c8h1w4(GLOBAL_SIZE_2_DIMS __private const int out_w_blocks,\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *kernel_ptr,\n" +" __global const FLOAT *bias_ptr,\n" +" __global FLOAT *output,\n" +" __private const int in_c_block,\n" +" __private const int out_h,\n" +" __private const int out_w,\n" +" __private const int out_c_block) {\n" +" const int out_c_w_idx=get_global_id(0); //c/8 w/4\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_h;//equal to in_h_idx\n" +" const int out_w4_idx=mul24(out_w_idx,4);\n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx<<1,bias_ptr));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=out0;\n" +" COMPUTE_FLOAT4 out3=out0;\n" +" \n" +" COMPUTE_FLOAT4 out4=CONVERT_COMPUTE_FLOAT4(vload4((out_c_idx<<1)+1,bias_ptr));\n" +" COMPUTE_FLOAT4 out5=out4;\n" +" COMPUTE_FLOAT4 out6=out4;\n" +" COMPUTE_FLOAT4 out7=out4;\n" +" const int intput_width_idx0=out_w4_idx;\n" +" \n" +" for (int in_channel_block_idx=0; in_channel_block_idx= 4) {\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,_tempoutput);\n" +" } else if (remain == 3) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,_tempoutput);\n" +" vstore4(CONVERT_FLOAT4(out2),2,_tempoutput);\n" +" } else if (remain == 2) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,_tempoutput);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(out0),0,_tempoutput);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx*2+1 >= out_c_block) {\n" +" return;\n" +" }\n" +"#endif\n" +" if (remain >= 4) {\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out4,out5,out6,out7)),0,_tempoutput1);\n" +" } else if (remain == 3) {\n" +" vstore8(CONVERT_FLOAT8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5))),0,_tempoutput1);\n" +" vstore4(CONVERT_FLOAT4(out6),2,_tempoutput1);\n" +" } else if (remain == 2) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,_tempoutput1);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(out4),0,_tempoutput1);\n" +" }\n" +"#else\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,_tempoutput);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx*2+1 >= out_c_block) {\n" +" return;\n" +" }\n" +"#endif\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out4,out5,out6,out7)),0,_tempoutput1);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_1x1_c8h1w2(GLOBAL_SIZE_2_DIMS __private const int out_w_blocks,\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *kernel_ptr,\n" +" __global const FLOAT *bias_ptr,\n" +" __global FLOAT *output,\n" +" __private const int in_c_block,\n" +" __private const int out_h,\n" +" __private const int out_w,\n" +" __private const int out_c_block) { // oc/4\n" +" const int out_c_w_idx=get_global_id(0); //c/8 w/4\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_h;//equal to in_h_idx\n" +" \n" +" const int out_w2_idx=mul24(out_w_idx,2);\n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx<<1,bias_ptr));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" \n" +" COMPUTE_FLOAT4 out4=CONVERT_COMPUTE_FLOAT4(vload4((out_c_idx<<1)+1,bias_ptr));\n" +" COMPUTE_FLOAT4 out5=out4;\n" +" const int intput_width_idx0=out_w2_idx;\n" +" \n" +" for (int in_channel_block_idx=0; in_channel_block_idx= 2) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,_tempoutput);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(out0),0,_tempoutput);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx*2+1 >= out_c_block) {\n" +" return;\n" +" }\n" +"#endif\n" +" if (remain >= 2) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,_tempoutput1);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(out4),0,_tempoutput1);\n" +" }\n" +"#else\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,_tempoutput);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx*2+1 >= out_c_block) {\n" +" return;\n" +" }\n" +"#endif\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,_tempoutput1);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_1x1_c4h1w1(GLOBAL_SIZE_2_DIMS __private const int out_w_blocks,\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *kernel_ptr,\n" +" __global const FLOAT *bias_ptr,\n" +" __global FLOAT *output,\n" +" __private const int in_c_block,\n" +" __private const int out_h,\n" +" __private const int out_w,\n" +" __private const int out_c_block) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w;\n" +" const int out_w_idx=out_c_w_idx % out_w;\n" +" const int out_b_idx=out_b_h_idx/out_h;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_h;//equal to in_h_idx\n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias_ptr));\n" +" const int intput_width_idx0=out_w_idx;\n" +" \n" +" for (int in_channel_block_idx=0; in_channel_block_idx= 2) {\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" } else if (remain == 1) {\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_c4h1w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *weight,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_hw.y;\n" +" const int out_w_idx=out_c_w_idx % out_hw.y;\n" +" const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" \n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" \n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int kh_start=select(0,(-in_h_idx_base+dilate_hw.x-1)/dilate_hw.x,in_h_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int in_h_idx_start=mad24(kh_start,dilate_hw.x,in_h_idx_base);\n" +" const int in_h_idx_end=min(mad24(filter_hw.x,dilate_hw.x,in_h_idx_base),in_hw.x);\n" +" \n" +" const int weight_oc_offset=out_c_blocks*filter_hw.x*filter_hw.y*4;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w0_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=(in_w1_idx<0 || in_w1_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w1_idx,input+inp_offset_base));\n" +" \n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset));\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset));\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset*2));\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset*3));\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" if(out_w_idx+1 >= out_hw.y) return;\n" +" vstore4(CONVERT_FLOAT4(out1),1,output+out_offset);\n" +"#else\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_c4h1w4(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *weight,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=(out_c_w_idx % out_w_blocks) << 2;\n" +" const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=out0;\n" +" COMPUTE_FLOAT4 out3=out0;\n" +" const int in_w0_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_w1_idx_base=in_w0_idx_base+stride_hw.y;\n" +" const int in_w2_idx_base=in_w1_idx_base+stride_hw.y;\n" +" const int in_w3_idx_base=in_w2_idx_base+stride_hw.y;\n" +" const int in_h_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" \n" +" const int kh_start=select(0,(-in_h_idx_base+dilate_hw.x-1)/dilate_hw.x,in_h_idx_base<0);\n" +" const int in_h_idx_start=mad24(kh_start,dilate_hw.x,in_h_idx_base);\n" +" const int in_h_idx_end=min(mad24(filter_hw.x,dilate_hw.x,in_h_idx_base),in_hw.x);\n" +" \n" +" const int weight_oc_offset=out_c_blocks*filter_hw.x*filter_hw.y*4;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w0_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=(in_w1_idx<0 || in_w1_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w1_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=(in_w2_idx<0 || in_w2_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w2_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=(in_w3_idx<0 || in_w3_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w3_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset));\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset));\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset*2));\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset*3));\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.y-out_w_idx;\n" +" if (remain >= 4) {\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_c4h4w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *weight,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=out_c_w_idx/out_w_blocks;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" +" const int out_h_idx=(out_b_h_idx % out_h_blocks) << 2;\n" +" \n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=out0;\n" +" COMPUTE_FLOAT4 out3=out0;\n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h0_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" const int in_h1_idx_base=in_h0_idx_base+stride_hw.x;\n" +" const int in_h2_idx_base=in_h1_idx_base+stride_hw.x;\n" +" const int in_h3_idx_base=in_h2_idx_base+stride_hw.x;\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int weight_oc_offset=out_c_blocks*filter_hw.x*filter_hw.y*4;\n" +" const int in_hw_size=in_hw.x*in_hw.y;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h0_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=(in_h1_idx<0 || in_h1_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h1_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=(in_h2_idx<0 || in_h2_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h2_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=(in_h3_idx<0 || in_h3_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h3_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset));\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset));\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset*2));\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset*3));\n" +" \n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" const int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.x-out_h_idx;\n" +" if(remain >= 4){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_c8h4w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *weight,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" +" const int out_h_idx=(out_b_h_idx % out_h_blocks) << 2;\n" +" \n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=out0;\n" +" COMPUTE_FLOAT4 out3=out0;\n" +" COMPUTE_FLOAT4 out4=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx+1,bias));\n" +" COMPUTE_FLOAT4 out5=out4;\n" +" COMPUTE_FLOAT4 out6=out4;\n" +" COMPUTE_FLOAT4 out7=out4;\n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h0_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" const int in_h1_idx_base=in_h0_idx_base+stride_hw.x;\n" +" const int in_h2_idx_base=in_h1_idx_base+stride_hw.x;\n" +" const int in_h3_idx_base=in_h2_idx_base+stride_hw.x;\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int weight_oc_offset=filter_hw.x*filter_hw.y*4;\n" +" const int weight_ic_offset=out_c_blocks*weight_oc_offset;\n" +" const int in_hw_size=in_hw.x*in_hw.y;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h0_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=(in_h1_idx<0 || in_h1_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h1_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=(in_h2_idx<0 || in_h2_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h2_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=(in_h3_idx<0 || in_h3_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h3_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset));\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset));\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset*2));\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset*3));\n" +" \n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset));\n" +" weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset));\n" +" weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*2));\n" +" weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*3));\n" +" out4=mad(in0.x,weight0,out4);\n" +" out4=mad(in0.y,weight1,out4);\n" +" out4=mad(in0.z,weight2,out4);\n" +" out4=mad(in0.w,weight3,out4);\n" +" \n" +" out5=mad(in1.x,weight0,out5);\n" +" out5=mad(in1.y,weight1,out5);\n" +" out5=mad(in1.z,weight2,out5);\n" +" out5=mad(in1.w,weight3,out5);\n" +" \n" +" out6=mad(in2.x,weight0,out6);\n" +" out6=mad(in2.y,weight1,out6);\n" +" out6=mad(in2.z,weight2,out6);\n" +" out6=mad(in2.w,weight3,out6);\n" +" \n" +" out7=mad(in3.x,weight0,out7);\n" +" out7=mad(in3.y,weight1,out7);\n" +" out7=mad(in3.z,weight2,out7);\n" +" out7=mad(in3.w,weight3,out7);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +" out4=fmax(out4,(COMPUTE_FLOAT4)0);\n" +" out5=fmax(out5,(COMPUTE_FLOAT4)0);\n" +" out6=fmax(out6,(COMPUTE_FLOAT4)0);\n" +" out7=fmax(out7,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out4=clamp(out4,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out5=clamp(out5,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out6=clamp(out6,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out7=clamp(out7,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.x-out_h_idx;\n" +" if(remain >= 4){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" if(remain >= 4){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out7),3*out_hw.y,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2*out_hw.y,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),3*out_hw.y,output+out_offset);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out5),out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2*out_hw.y,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out7),3*out_hw.y,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_c8h2w1(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *weight,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=out_c_w_idx % out_w_blocks;\n" +" const int out_b_idx=out_b_h_idx/out_h_blocks;//equal to in_b_idx\n" +" const int out_h_idx=(out_b_h_idx % out_h_blocks) << 1;\n" +" \n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx+1,bias));\n" +" COMPUTE_FLOAT4 out3=out2;\n" +" const int in_w_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_h0_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" const int in_h1_idx_base=in_h0_idx_base+stride_hw.x;\n" +" \n" +" const int kw_start=select(0,(-in_w_idx_base+dilate_hw.y-1)/dilate_hw.y,in_w_idx_base<0);\n" +" const int in_w_idx_start=mad24(kw_start,dilate_hw.y,in_w_idx_base);\n" +" const int in_w_idx_end=min(mad24(filter_hw.y,dilate_hw.y,in_w_idx_base),in_hw.y);\n" +" \n" +" const int weight_oc_offset=filter_hw.x*filter_hw.y*4;\n" +" const int weight_ic_offset=out_c_blocks*weight_oc_offset;\n" +" const int in_hw_size=in_hw.x*in_hw.y;\n" +" // weight: [ic/4,oc,4],loop: ic/4\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h0_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=(in_h1_idx<0 || in_h1_idx >= in_hw_size) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_h1_idx+fw,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset));\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset));\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset*2));\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset*3));\n" +" \n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset));\n" +" weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset));\n" +" weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*2));\n" +" weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*3));\n" +" \n" +" out2=mad(in0.x,weight0,out2);\n" +" out2=mad(in0.y,weight1,out2);\n" +" out2=mad(in0.z,weight2,out2);\n" +" out2=mad(in0.w,weight3,out2);\n" +" \n" +" out3=mad(in1.x,weight0,out3);\n" +" out3=mad(in1.y,weight1,out3);\n" +" out3=mad(in1.z,weight2,out3);\n" +" out3=mad(in1.w,weight3,out3);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.x-out_h_idx;\n" +" if(remain >= 2){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" if(remain >= 2){\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),out_hw.y,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out1),out_hw.y,output+out_offset);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks){\n" +" return;\n" +" }\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore4(CONVERT_FLOAT4(out2),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out3),out_hw.y,output+out_offset);\n" +"#endif\n" +"}\n" +"__kernel\n" +"void conv_2d_c8h1w4(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input,\n" +" __global const FLOAT *weight,\n" +" __global const FLOAT *bias,\n" +" __global FLOAT *output,\n" +" __private const int2 in_hw,\n" +" __private const int inChannel,\n" +" __private const int in_c_blocks,\n" +" __private const int2 out_hw,\n" +" __private const int2 filter_hw,\n" +" __private const int2 stride_hw,\n" +" __private const int2 pad_hw,\n" +" __private const int2 dilate_hw,\n" +" __private const int out_w_blocks,\n" +" __private const int out_c_blocks,\n" +" __private const int out_h_blocks) {\n" +" const int out_c_w_idx=get_global_id(0); //c/4 w\n" +" const int out_b_h_idx=get_global_id(1); //b h\n" +" DEAL_NON_UNIFORM_DIM2(out_c_w_idx,out_b_h_idx);\n" +" const int out_c_idx=(out_c_w_idx/out_w_blocks) << 1;\n" +" const int out_w_idx=(out_c_w_idx % out_w_blocks) << 2;\n" +" const int out_b_idx=out_b_h_idx/out_hw.x;//equal to in_b_idx\n" +" const int out_h_idx=out_b_h_idx % out_hw.x;\n" +" \n" +" COMPUTE_FLOAT4 out0=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx,bias));\n" +" COMPUTE_FLOAT4 out1=out0;\n" +" COMPUTE_FLOAT4 out2=out0;\n" +" COMPUTE_FLOAT4 out3=out0;\n" +" \n" +" COMPUTE_FLOAT4 out4=CONVERT_COMPUTE_FLOAT4(vload4(out_c_idx+1,bias));\n" +" COMPUTE_FLOAT4 out5=out4;\n" +" COMPUTE_FLOAT4 out6=out4;\n" +" COMPUTE_FLOAT4 out7=out4;\n" +" const int in_w0_idx_base=mad24(out_w_idx,stride_hw.y,-pad_hw.y);\n" +" const int in_w1_idx_base=in_w0_idx_base+stride_hw.y;\n" +" const int in_w2_idx_base=in_w1_idx_base+stride_hw.y;\n" +" const int in_w3_idx_base=in_w2_idx_base+stride_hw.y;\n" +" const int in_h_idx_base=mad24(out_h_idx,stride_hw.x,-pad_hw.x);\n" +" \n" +" const int kh_start=select(0,(-in_h_idx_base+dilate_hw.x-1)/dilate_hw.x,in_h_idx_base<0);\n" +" const int in_h_idx_start=mad24(kh_start,dilate_hw.x,in_h_idx_base);\n" +" const int in_h_idx_end=min(mad24(filter_hw.x,dilate_hw.x,in_h_idx_base),in_hw.x);\n" +" \n" +" const int weight_oc_offset=filter_hw.x*filter_hw.y*4;\n" +" const int weight_ic_offset=out_c_blocks*weight_oc_offset;\n" +" for(ushort in_c_idx=0; in_c_idx= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w0_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in1=(in_w1_idx<0 || in_w1_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w1_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in2=(in_w2_idx<0 || in_w2_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w2_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 in3=(in_w3_idx<0 || in_w3_idx >= in_hw.y) ? (COMPUTE_FLOAT4)0 : CONVERT_COMPUTE_FLOAT4(vload4(in_w3_idx,input+inp_offset_base));\n" +" COMPUTE_FLOAT4 weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset));\n" +" COMPUTE_FLOAT4 weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset));\n" +" COMPUTE_FLOAT4 weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset*2));\n" +" COMPUTE_FLOAT4 weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_ic_offset*3));\n" +" out0=mad(in0.x,weight0,out0);\n" +" out0=mad(in0.y,weight1,out0);\n" +" out0=mad(in0.z,weight2,out0);\n" +" out0=mad(in0.w,weight3,out0);\n" +" \n" +" out1=mad(in1.x,weight0,out1);\n" +" out1=mad(in1.y,weight1,out1);\n" +" out1=mad(in1.z,weight2,out1);\n" +" out1=mad(in1.w,weight3,out1);\n" +" \n" +" out2=mad(in2.x,weight0,out2);\n" +" out2=mad(in2.y,weight1,out2);\n" +" out2=mad(in2.z,weight2,out2);\n" +" out2=mad(in2.w,weight3,out2);\n" +" \n" +" out3=mad(in3.x,weight0,out3);\n" +" out3=mad(in3.y,weight1,out3);\n" +" out3=mad(in3.z,weight2,out3);\n" +" out3=mad(in3.w,weight3,out3);\n" +" \n" +" weight0=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset));\n" +" weight1=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset));\n" +" weight2=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*2));\n" +" weight3=CONVERT_COMPUTE_FLOAT4(vload4(0,weight+weight_offset+weight_oc_offset+weight_ic_offset*3));\n" +" \n" +" out4=mad(in0.x,weight0,out4);\n" +" out4=mad(in0.y,weight1,out4);\n" +" out4=mad(in0.z,weight2,out4);\n" +" out4=mad(in0.w,weight3,out4);\n" +" \n" +" out5=mad(in1.x,weight0,out5);\n" +" out5=mad(in1.y,weight1,out5);\n" +" out5=mad(in1.z,weight2,out5);\n" +" out5=mad(in1.w,weight3,out5);\n" +" \n" +" out6=mad(in2.x,weight0,out6);\n" +" out6=mad(in2.y,weight1,out6);\n" +" out6=mad(in2.z,weight2,out6);\n" +" out6=mad(in2.w,weight3,out6);\n" +" \n" +" out7=mad(in3.x,weight0,out7);\n" +" out7=mad(in3.y,weight1,out7);\n" +" out7=mad(in3.z,weight2,out7);\n" +" out7=mad(in3.w,weight3,out7);\n" +" \n" +" weight_offset += 4;\n" +" }\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" out0=fmax(out0,(COMPUTE_FLOAT4)0);\n" +" out1=fmax(out1,(COMPUTE_FLOAT4)0);\n" +" out2=fmax(out2,(COMPUTE_FLOAT4)0);\n" +" out3=fmax(out3,(COMPUTE_FLOAT4)0);\n" +" out4=fmax(out4,(COMPUTE_FLOAT4)0);\n" +" out5=fmax(out5,(COMPUTE_FLOAT4)0);\n" +" out6=fmax(out6,(COMPUTE_FLOAT4)0);\n" +" out7=fmax(out7,(COMPUTE_FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" out0=clamp(out0,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out1=clamp(out1,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out2=clamp(out2,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out3=clamp(out3,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out4=clamp(out4,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out5=clamp(out5,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out6=clamp(out6,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +" out7=clamp(out7,(COMPUTE_FLOAT4)0,(COMPUTE_FLOAT4)6);\n" +"#endif\n" +" int out_offset=(((out_b_idx*out_c_blocks+out_c_idx)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +"#ifdef BLOCK_LEAVE\n" +" const int remain=out_hw.y-out_w_idx;\n" +" if(remain >= 4){\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out2),2,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out0,out1)),0,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out0),0,output+out_offset);\n" +" }\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks)return;\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" if(remain >= 4){\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out4,out5,out6,out7)),0,output+out_offset);\n" +" }else if(remain == 3){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,output+out_offset);\n" +" vstore4(CONVERT_FLOAT4(out6),2,output+out_offset);\n" +" }else if(remain == 2){\n" +" vstore8(CONVERT_FLOAT8((COMPUTE_FLOAT8)(out4,out5)),0,output+out_offset);\n" +" }else if(remain == 1){\n" +" vstore4(CONVERT_FLOAT4(out4),0,output+out_offset);\n" +" }\n" +"#else\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out0,out1,out2,out3)),0,output+out_offset);\n" +"#ifdef CHANNEL_LEAVE\n" +" if(out_c_idx+1 >= out_c_blocks)return;\n" +"#endif\n" +" out_offset=(((out_b_idx*out_c_blocks+out_c_idx+1)*out_hw.x+out_h_idx)*out_hw.y+out_w_idx)*4;\n" +" vstore16(CONVERT_FLOAT16((COMPUTE_FLOAT16)(out4,out5,out6,out7)),0,output+out_offset);\n" +"#endif\n" +"}\n" +; +#endif +const char* buffer_to_image = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"// convert kernel : from buffer(oi ) to image(oc,ic/4)\n" +"__kernel void conv2d1x1_opt_filter_buffer_to_image(GLOBAL_SIZE_2_DIMS __global const FLOAT *input_ptr,\n" +" __private const int input_channel,__private const int2 kernel_shape,__private const int ic_h_w_size,\n" +" __private const int height_width_size,__write_only image2d_t output) {\n" +" \n" +" int ic_4_idx=get_global_id(0); // ic/4\n" +" int oc_idx=get_global_id(1); // oc\n" +" DEAL_NON_UNIFORM_DIM2(ic_4_idx,oc_idx);\n" +" const int ic_idx=ic_4_idx*4;\n" +" const int buffer_offset=oc_idx*input_channel+ic_idx;\n" +" \n" +" FLOAT4 output_values=0;\n" +" if (ic_idx= 4) {\n" +" output_values.x=*(input_ptr+buffer_offset);\n" +" output_values.y=*(input_ptr+buffer_offset+1);\n" +" output_values.z=*(input_ptr+buffer_offset+2);\n" +" output_values.w=*(input_ptr+buffer_offset+3);\n" +" } else if (remain_channel == 3) {\n" +" output_values.x=*(input_ptr+buffer_offset);\n" +" output_values.y=*(input_ptr+buffer_offset+1);\n" +" output_values.z=*(input_ptr+buffer_offset+2);\n" +" output_values.w=0;\n" +" } else if (remain_channel == 2) {\n" +" output_values.x=*(input_ptr+buffer_offset);\n" +" output_values.y=*(input_ptr+buffer_offset+1);\n" +" output_values.z=0;\n" +" output_values.w=0;\n" +" } else if (remain_channel == 1) {\n" +" output_values.x=*(input_ptr+buffer_offset);\n" +" output_values.y=0;\n" +" output_values.z=0;\n" +" output_values.w=0;\n" +" }\n" +" }\n" +" WI_F(output,(int2)(ic_4_idx,oc_idx),output_values);\n" +"}\n" +"// convert kernel : from buffer(oihw) to image(oc/4 h w ,ic oc4)\n" +"__kernel void conv2d_filter_buffer_to_image(GLOBAL_SIZE_2_DIMS\n" +" #ifdef BUFFER_INP_FP32\n" +" __global const float *input_ptr,\n" +" #else\n" +" __global const FLOAT *input_ptr,\n" +" #endif\n" +" __private const int output_channel,__private const int2 kernel_shape,__private const int ic_h_w_size,\n" +" __private const int height_width_size,__write_only image2d_t output) {\n" +" int image_width_idx=get_global_id(0); // ic\n" +" int image_height_idx=get_global_id(1); // oc/4 h w\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int input_channel_4_idx=image_width_idx;\n" +" const int output_channel_4_idx=(image_height_idx/height_width_size)*4;\n" +" const int height_width_idx=image_height_idx % height_width_size;\n" +" const int buffer_height_idx=height_width_idx/kernel_shape.y;\n" +" const int buffer_width_idx=height_width_idx % kernel_shape.y;\n" +" const int buffer_offset=output_channel_4_idx*ic_h_w_size+input_channel_4_idx*height_width_size +\n" +" buffer_height_idx*kernel_shape.y+buffer_width_idx;\n" +" FLOAT4 output_values=0;\n" +" if (output_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.w=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" WI_F(output,(int2)(image_width_idx,image_height_idx),output_values);\n" +"}\n" +"// only for debug\n" +"// convert kernel : from image(oc/4 h w ,ic oc4) to buffer(oihw)\n" +"__kernel void conv2d_filter_image_to_buffer(GLOBAL_SIZE_2_DIMS __global FLOAT *output_ptr,\n" +" __private const int output_channel,__private const int2 kernel_shape,\n" +" __private const int ic_h_w_size,\n" +" __private const int height_width_size,__read_only image2d_t input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int input_channel_4_idx=image_width_idx;\n" +" const int output_channel_4_idx=image_height_idx/height_width_size*4;\n" +" const int height_width_idx=image_height_idx % height_width_size;\n" +" const int buffer_height_idx=height_width_idx/kernel_shape.y;\n" +" const int buffer_width_idx=height_width_idx % kernel_shape.y;\n" +" const int buffer_offset=output_channel_4_idx*ic_h_w_size+input_channel_4_idx*height_width_size +\n" +" buffer_height_idx*kernel_shape.y+buffer_width_idx;\n" +" if (output_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_ptr[offset]=values.x;\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_ptr[offset]=values.y;\n" +" offset += ic_h_w_size;\n" +" output_ptr[offset]=values.z;\n" +" offset += ic_h_w_size;\n" +" output_ptr[offset]=values.w;\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_ptr[offset]=values.x;\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_ptr[offset]=values.y;\n" +" offset += ic_h_w_size;\n" +" output_ptr[offset]=values.z;\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_ptr[offset]=values.x;\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_ptr[offset]=values.y;\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_ptr[offset]=values.x;\n" +" }\n" +" }\n" +"}\n" +"// convert kernel from buffer(mihw) to image(ic/4,ic4 h w m)\n" +"// but now dw only support m == 1\n" +"__kernel void dw_filter_buffer_to_image(GLOBAL_SIZE_2_DIMS\n" +" #ifdef BUFFER_INP_FP32\n" +" __global const float *input_ptr,\n" +" #else\n" +" __global const FLOAT *input_ptr,\n" +" #endif\n" +" __private const int4 kernel_shape,\n" +" __private const int height_width_size,__write_only image2d_t output) {\n" +" const int image_width_idx=get_global_id(0);\n" +" const int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" FLOAT4 output_values=0;\n" +" if (kernel_shape.x == 1) {\n" +" const int input_channel_4_idx=image_height_idx*4;\n" +" const int buffer_height_idx=image_width_idx/kernel_shape.w;\n" +" const int buffer_width_idx=image_width_idx % kernel_shape.w;\n" +" const int buffer_offset =\n" +" mad24(mad24(input_channel_4_idx,kernel_shape.z,buffer_height_idx),kernel_shape.w,buffer_width_idx);\n" +" const int remain_channel=kernel_shape.y-input_channel_4_idx;\n" +" if (input_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.w=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" }\n" +" WI_F(output,(int2)(image_width_idx,image_height_idx),output_values);\n" +"}\n" +"__kernel void nc4hw4_buffer_to_image(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int2 output_shape,\n" +" __private const int batch_size,__write_only image2d_t output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/output_shape.x;\n" +" const int height_idx=image_height_idx % output_shape.x;\n" +" const int width_idx=image_width_idx % output_shape.y;\n" +" const int channel_block_idx=image_width_idx/output_shape.y;\n" +" int buffer_offset =\n" +" (((batch_idx+channel_block_idx*batch_size)*output_shape.x+height_idx)*output_shape.y+width_idx)*4;\n" +" int2 coord=(int2)(image_width_idx,image_height_idx);\n" +" WI_DATA(output,coord,CONVERT_OUTPUT_I4(vload4(0,input_ptr+buffer_offset)));\n" +"}\n" +"__kernel void image_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int2 output_shape,\n" +" __private const int batch_size,\n" +" __read_only image2d_t input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/output_shape.x;\n" +" const int height_idx=image_height_idx % output_shape.x;\n" +" const int width_idx=image_width_idx % output_shape.y;\n" +" int channel_block_idx=image_width_idx/output_shape.y;\n" +" int buffer_offset =\n" +" (((batch_idx+channel_block_idx*batch_size)*output_shape.x+height_idx)*output_shape.y+width_idx)*4;\n" +" int2 coord=(int2)(image_width_idx,image_height_idx);\n" +" vstore4(CONVERT_OUTPUT4(RI_DATA(input_ptr,SAMPLER,coord)),0,output+buffer_offset);\n" +"}\n" +"__kernel void nhwc_buffer_to_image(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int height,\n" +" __private const int width,__private const int channels,\n" +" __write_only image2d_t output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_4_idx=(image_width_idx/width) << 2;\n" +" const int buffer_offset=((batch_idx*height+height_idx)*width+width_idx)*channels+channel_4_idx;\n" +" const int remain_channel=channels-channel_4_idx;\n" +" INPUT_TYPE4 values=vload4(0,input_ptr+buffer_offset);\n" +" if (remain_channel == 3) {\n" +" values.w=0;\n" +" } else if (remain_channel == 2) {\n" +" values.z=0;\n" +" values.w=0;\n" +" } else if (remain_channel == 1) {\n" +" values.y=0;\n" +" values.z=0;\n" +" values.w=0;\n" +" }\n" +" WI_DATA(output,(int2)(image_width_idx,image_height_idx),CONVERT_OUTPUT_I4(values));\n" +"}\n" +"__kernel void nchw_buffer_to_image(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int height,__private const int width,__private const int channels,\n" +" __write_only image2d_t output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_4_idx=image_width_idx/width << 2;\n" +" const int buffer_offset=((batch_idx*channels+channel_4_idx)*height+height_idx)*width+width_idx;\n" +" const int remain_channel=channels-channel_4_idx;\n" +" const int height_width_size=height*width;\n" +" INPUT_TYPE4 output_values=0;\n" +" if (remain_channel >= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.y=*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.z=*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.w=*(input_ptr+offset);\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.y=*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.z=*(input_ptr+offset);\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.y=*(input_ptr+offset);\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=*(input_ptr+offset);\n" +" }\n" +" WI_DATA(output,(int2)(image_width_idx,image_height_idx),CONVERT_OUTPUT_I4(output_values));\n" +"}\n" +"__kernel void image_to_nhwc_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int height,__private const int width,\n" +" __private const int channels,\n" +" __read_only image2d_t input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_4_idx=(image_width_idx/width) << 2;\n" +" const int buffer_offset=((batch_idx*height+height_idx)*width+width_idx)*channels+channel_4_idx;\n" +" int2 coord=(int2)(image_width_idx,image_height_idx);\n" +" \n" +" INPUT_TYPE_I4 values=RI_DATA(input_ptr,SAMPLER,coord);\n" +" const int remain_channel=channels-channel_4_idx;\n" +" if (remain_channel >= 4) {\n" +" vstore4(CONVERT_OUTPUT4(values),0,output+buffer_offset);\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" }\n" +"}\n" +"__kernel void image_to_nchw_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int height,__private const int width,\n" +" __private const int channels,\n" +" __read_only image2d_t input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" int channel_4_idx=(image_width_idx/width)*4;\n" +" int buffer_offset=((batch_idx*channels+channel_4_idx)*height+height_idx)*width+width_idx;\n" +" \n" +" INPUT_TYPE_I4 values=RI_DATA(input_ptr,SAMPLER,(int2)(image_width_idx,image_height_idx));\n" +" const int height_width_size=height*width;\n" +" const int remain_channel=channels-channel_4_idx;\n" +" if (remain_channel >= 4) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.w;\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" }\n" +"}\n" +"// convert arg as 4 alignment\n" +"__kernel void arg_buffer_to_image(GLOBAL_SIZE_2_DIMS __global const INPUT_TYPE *input_ptr,__private const int count,\n" +" __write_only image2d_t output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int buffer_4_offset=image_width_idx << 2;\n" +" const int remain=count-buffer_4_offset;\n" +" int offset=buffer_4_offset;\n" +" INPUT_TYPE4 values=0;\n" +" if (remain >= 4) {\n" +" values=vload4(0,input_ptr+offset);\n" +" } else if (remain == 3) {\n" +" values.x=*(input_ptr+offset);\n" +" offset++;\n" +" values.y=*(input_ptr+offset);\n" +" offset++;\n" +" values.z=*(input_ptr+offset);\n" +" } else if (remain == 2) {\n" +" values.x=*(input_ptr+offset);\n" +" offset++;\n" +" values.y=*(input_ptr+offset);\n" +" } else if (remain == 1) {\n" +" values.x=*(input_ptr+offset);\n" +" }\n" +" WI_DATA(output,(int2)(image_width_idx,image_height_idx),CONVERT_OUTPUT_I4(values));\n" +"}\n" +"// only for debug\n" +"__kernel void arg_image_to_buffer(GLOBAL_SIZE_2_DIMS __global OUTPUT_TYPE *output,__private const int count,\n" +" __read_only image2d_t input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int buffer_4_offset=image_width_idx << 2;\n" +" int2 coord=(int2)(image_width_idx,image_height_idx);\n" +" INPUT_TYPE_I4 values=RI_DATA(input_ptr,SAMPLER,coord);\n" +" const int remain=count-buffer_4_offset;\n" +" if (remain<4) {\n" +" switch (remain) {\n" +" case 3:\n" +" output[buffer_4_offset+2]=(OUTPUT_TYPE)values.s2;\n" +" case 2:\n" +" output[buffer_4_offset+1]=(OUTPUT_TYPE)values.s1;\n" +" case 1:\n" +" output[buffer_4_offset]=(OUTPUT_TYPE)values.s0;\n" +" }\n" +" } else {\n" +" vstore4(CONVERT_OUTPUT4(values),0,output+buffer_4_offset);\n" +" }\n" +" if (remain >= 4) {\n" +" vstore4(CONVERT_OUTPUT4(values),0,output+buffer_4_offset);\n" +" } else if (remain == 3) {\n" +" int offset=buffer_4_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" } else if (remain == 2) {\n" +" int offset=buffer_4_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" } else if (remain == 1) {\n" +" int offset=buffer_4_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" }\n" +"}\n" +; +const char* winogradTransformDest2_3_1 = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void winogradTransformDest(__read_only image2d_t uInput,// 0\n" +" __read_only image2d_t uBias,__write_only image2d_t uOutput,\n" +" __private const int unitWidth,// 3\n" +" __private const int unitHeight,__private const int dstWidth,\n" +" __private const int dstHeight,// 6\n" +" __private const int dstChannelC4,__private const int batchOffset) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));\n" +" if (pos.x0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid> 2;\n" +" const int inside_remain=inside-((inside_v4-1) << 2);\n" +" COMPUTE_FLOAT4 in_sum=0;\n" +" int index=lid;\n" +" for(; index1) {\n" +" sum[lid]=sum[lid]+in_left.y;\n" +" }\n" +" if(inside_remain>2) {\n" +" sum[lid]=sum[lid]+in_left.z;\n" +" }\n" +" if(inside_remain>3) {\n" +" sum[lid]=sum[lid]+in_left.w;\n" +" }\n" +" }\n" +" \n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (lid1) {\n" +" sum[lid]=sum[lid]+in_sum.y;\n" +" }\n" +" if(inside_remain>2) {\n" +" sum[lid]=sum[lid]+in_sum.z;\n" +" }\n" +" if(inside_remain>3) {\n" +" sum[lid]=sum[lid]+in_sum.w;\n" +" }\n" +" }\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" for(int i=LOCAL_SIZE/2; i>0; i /= 2){\n" +" if (lid= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void softmax_channel(GLOBAL_SIZE_3_DIMS\n" +" __global const FLOAT *input,\n" +" __global FLOAT *output,\n" +" __private const int remain_channels,\n" +" __private const int4 shape) {//NCHW\n" +" const int x=get_global_id(0);\n" +" const int w=get_global_id(1);\n" +" const int bh=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(x,w,bh);\n" +" \n" +" const int batch_idx=bh/shape.z;\n" +" const int height_idx=bh % shape.z;\n" +" const int offset=(((batch_idx*shape.y+0)*shape.z+height_idx)*shape.w+w)*4;\n" +"#if SOFTMAX_LOCAL_SIZE >= 4\n" +" int lid=get_local_id(0);\n" +" COMPUTE_FLOAT4 local sum[SOFTMAX_LOCAL_SIZE];\n" +" COMPUTE_FLOAT4 maxValue=(COMPUTE_FLOAT4)-FLT_MAX;\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= 4\n" +" int lid=get_local_id(0);\n" +" COMPUTE_FLOAT4 local sum[SOFTMAX_LOCAL_SIZE];\n" +" \n" +" /*Compute Max */\n" +" COMPUTE_FLOAT4 maxValue=(COMPUTE_FLOAT4)(-FLT_MAX);\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= 4\n" +" int lid=get_local_id(0);\n" +" COMPUTE_FLOAT4 local sum[SOFTMAX_LOCAL_SIZE];\n" +" \n" +" /*Compute Max */\n" +" COMPUTE_FLOAT4 maxValue=(COMPUTE_FLOAT4)(-FLT_MAX);\n" +" for (int i=lid; i0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid> 2;\n" +" #ifdef GATHER_INPUT_NHWC\n" +" int off_c=offset_value % offset_dst_shape.z; offset_value /= offset_dst_shape.z;\n" +" int off_w=offset_value % offset_dst_shape.x; offset_value /= offset_dst_shape.x;\n" +" int off_h=offset_value % offset_dst_shape.y;\n" +" int off_b=offset_value/offset_dst_shape.y;\n" +" #else\n" +" int off_w=offset_value % offset_dst_shape.x; offset_value /= offset_dst_shape.x;\n" +" int off_h=offset_value % offset_dst_shape.y; offset_value /= offset_dst_shape.y;\n" +" int off_c=offset_value % offset_dst_shape.z;\n" +" int off_b=offset_value/offset_dst_shape.z;\n" +" #endif\n" +" int real_dst_offset=(((off_b*off_c4_size+off_c/4)*offset_dst_shape.y+off_h)*offset_dst_shape.x+off_w)*4+off_c % 4;\n" +" index.x=offset_dst_ptr[real_dst_offset];\n" +" }\n" +" #endif\n" +" \n" +" #ifdef OFFSET_SRC\n" +" {\n" +" int offset_value=pos.z;\n" +" int off_c4_size=(offset_src_shape.z+3) >> 2;\n" +" #ifdef GATHER_INPUT_NHWC\n" +" int off_c=offset_value % offset_src_shape.z; offset_value /= offset_src_shape.z;\n" +" int off_w=offset_value % offset_src_shape.x; offset_value /= offset_src_shape.x;\n" +" int off_h=offset_value % offset_src_shape.y;\n" +" int off_b=offset_value/offset_src_shape.y;\n" +" #else\n" +" int off_w=offset_value % offset_src_shape.x; offset_value /= offset_src_shape.x;\n" +" int off_h=offset_value % offset_src_shape.y; offset_value /= offset_src_shape.y;\n" +" int off_c=offset_value % offset_src_shape.z;\n" +" int off_b=offset_value/offset_src_shape.z;\n" +" #endif\n" +" int real_src_offset=(((off_b*off_c4_size+off_c/4)*offset_src_shape.y+off_h)*offset_src_shape.x+off_w)*4+off_c % 4;\n" +" index.y=offset_src_ptr[real_src_offset];\n" +" }\n" +" #endif\n" +" \n" +" int2 offset=index*steps;\n" +" int src_offset=offset.y+stride_src.w+x*stride_src.x+y*stride_src.y+pos.y*stride_src.z;\n" +" int dst_offset=offset.x+stride_dst.w+x*stride_dst.x+y*stride_dst.y+pos.y*stride_dst.z;\n" +" int src_offsetC4,dst_offsetC4;\n" +" {\n" +"#ifdef GATHER_INPUT_NHWC\n" +" int c=src_offset % src_c4size.z; src_offset /= src_c4size.z;\n" +" int w=src_offset % src_c4size.x; src_offset /= src_c4size.x;\n" +" int h=src_offset % src_c4size.y;\n" +" int b=src_offset/src_c4size.y;\n" +" int c4_size=(src_c4size.z+3)/4;\n" +" src_offsetC4=(((b*c4_size+(c/4))*src_c4size.y+h)*src_c4size.x+w)*4+(c % 4);\n" +"#else\n" +" int w=src_offset % src_c4size.x; src_offset /= src_c4size.x;\n" +" int h=src_offset % src_c4size.y; src_offset /= src_c4size.y;\n" +" int c=src_offset % src_c4size.z;\n" +" int b=src_offset/src_c4size.z;\n" +" int c4_size=(src_c4size.z+3)/4;\n" +" src_offsetC4=(((b*c4_size+(c/4))*src_c4size.y+h)*src_c4size.x+w)*4+(c % 4);\n" +"#endif\n" +" }\n" +" {\n" +"#ifdef GATHER_OUTPUT_NHWC\n" +" int c=dst_offset % dst_c4size.z; dst_offset /= dst_c4size.z;\n" +" int w=dst_offset % dst_c4size.x; dst_offset /= dst_c4size.x;\n" +" int h=dst_offset % dst_c4size.y;\n" +" int b=dst_offset/dst_c4size.y;\n" +" int c4_size=(dst_c4size.z+3)/4;\n" +" dst_offsetC4=(((b*c4_size+(c/4))*dst_c4size.y+h)*dst_c4size.x+w)*4+(c % 4);\n" +"#else\n" +" int w=dst_offset % dst_c4size.x; dst_offset /= dst_c4size.x;\n" +" int h=dst_offset % dst_c4size.y; dst_offset /= dst_c4size.y;\n" +" int c=dst_offset % dst_c4size.z;\n" +" int b=dst_offset/dst_c4size.z;\n" +" int c4_size=(dst_c4size.z+3)/4;\n" +" dst_offsetC4=(((b*c4_size+(c/4))*dst_c4size.y+h)*dst_c4size.x+w)*4+(c % 4);\n" +"#endif\n" +" }\n" +" if(offset.x >= 0){\n" +" if(offset.y >= 0 && offset.y1\n" +" __local COMPUTE_FLOAT2 sum[WORK_GROUP_SIZE];\n" +"#endif\n" +"#if SLM_DIV_FACTOR>1\n" +" for (int icb=feature_sub_block*IC_BLOCKS/SLM_DIV_FACTOR; icb<(feature_sub_block+1)*IC_BLOCKS/SLM_DIV_FACTOR; icb++) {\n" +"#else\n" +" for (int icb=0; icb= input_height)\n" +" continue;\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" {\n" +" int xb=0;\n" +" for (; xb+8 <= INPUT_LINE_SIZE; xb += 8) {\n" +" COMPUTE_FLOAT8 tmp=CONVERT_COMPUTE_FLOAT8(GROUP_READ8(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" line_cache[xb+4]=tmp[4];\n" +" line_cache[xb+5]=tmp[5];\n" +" line_cache[xb+6]=tmp[6];\n" +" line_cache[xb+7]=tmp[7];\n" +" }\n" +" for (; xb+4 <= INPUT_LINE_SIZE; xb += 4) {\n" +" COMPUTE_FLOAT4 tmp=CONVERT_COMPUTE_FLOAT4(GROUP_READ4(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" }\n" +" for (; xb1\n" +" sum[lid1]=dst;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" if (feature_sub_block == 0) {\n" +" __attribute__((opencl_unroll_hint)) for(int i=1; i= output_channel) {\n" +" for (int i=0; i<2 && (x+i)1\n" +" }\n" +"#endif\n" +"}\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_2d_buf_subgroup_c16_c4_b4(\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __global FLOAT* weights,\n" +" __global FLOAT* biases,\n" +" __private const int pad_width,\n" +" __private const int pad_height,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int output_width,\n" +" __private const int output_height,\n" +" __private const int output_channel,\n" +" __private const int x_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right\n" +") {\n" +" const int sglid=get_sub_group_local_id();\n" +" const int b=(uint)get_global_id(2);\n" +" const int xy=get_global_id(0);\n" +" const int x=(xy % x_blocks) << 2;\n" +" const int y=(xy/x_blocks);\n" +" const int lid1=(int)get_local_id(1);\n" +" const int feature_per_wg=(int)get_local_size(1)/SLM_DIV_FACTOR;\n" +" const int feature_sub_block=lid1/feature_per_wg;\n" +" const int feature_block=(int)get_group_id(1);\n" +" const int input_x=x*STRIDE_WIDTH-pad_width;\n" +" const int input_y=y*STRIDE_HEIGHT-pad_height;\n" +" const uint input_x_pitch=16;\n" +" const uint input_y_pitch=input_x_pitch*(input_pad_left+input_width+input_pad_right);\n" +" const uint input_fs_pitch=input_y_pitch*(input_height);\n" +" const uint input_b_pitch=input_fs_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint input_offset=b*input_b_pitch +\n" +" input_y*input_y_pitch +\n" +" (input_x+input_pad_left)*input_x_pitch;\n" +" const uint output_x_pitch=4;\n" +" const uint output_y_pitch=output_x_pitch*output_width;\n" +" const uint output_fs_pitch=output_y_pitch*output_height;\n" +" const uint output_b_pitch=output_fs_pitch*((output_channel+3)/4);\n" +" const uint output_offset=b*output_b_pitch +\n" +" (feature_block << 2)*output_fs_pitch +\n" +" y*output_y_pitch +\n" +" x*output_x_pitch;\n" +" const uint filter_isv_pitch=16;\n" +" const uint filter_x_pitch=16*16;\n" +" const uint filter_y_pitch=filter_x_pitch*FILTER_WIDTH;\n" +" const uint filter_is_pitch=filter_y_pitch*FILTER_HEIGHT;\n" +" const uint filter_os_pitch=filter_is_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint filter_offset=feature_block*filter_os_pitch;\n" +"#if SLM_DIV_FACTOR == 1\n" +" COMPUTE_FLOAT4 dst=(COMPUTE_FLOAT4)((GROUP_READ(biases,feature_block*16)));\n" +"#else\n" +" COMPUTE_FLOAT4 dst;\n" +" if (feature_sub_block == 0) {\n" +" dst=(COMPUTE_FLOAT4)((GROUP_READ(biases,feature_block*16)));\n" +" } else {\n" +" dst=(COMPUTE_FLOAT4)0;\n" +" }\n" +"#endif \n" +"#if SLM_DIV_FACTOR>1\n" +" __local COMPUTE_FLOAT4 sum[WORK_GROUP_SIZE];\n" +"#endif\n" +"#if SLM_DIV_FACTOR>1\n" +" for (int icb=feature_sub_block*IC_BLOCKS/SLM_DIV_FACTOR; icb<(feature_sub_block+1)*IC_BLOCKS/SLM_DIV_FACTOR; icb++) {\n" +"#else\n" +" for (int icb=0; icb= input_height)\n" +" continue;\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" {\n" +" int xb=0;\n" +" for (; xb+8 <= INPUT_LINE_SIZE; xb += 8) {\n" +" COMPUTE_FLOAT8 tmp=CONVERT_COMPUTE_FLOAT8(GROUP_READ8(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" line_cache[xb+4]=tmp[4];\n" +" line_cache[xb+5]=tmp[5];\n" +" line_cache[xb+6]=tmp[6];\n" +" line_cache[xb+7]=tmp[7];\n" +" }\n" +" for (; xb+4 <= INPUT_LINE_SIZE; xb += 4) {\n" +" COMPUTE_FLOAT4 tmp=CONVERT_COMPUTE_FLOAT4(GROUP_READ4(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" }\n" +" for (; xb1\n" +" sum[lid1]=dst;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" if (feature_sub_block == 0) {\n" +" __attribute__((opencl_unroll_hint)) for(int i=1; i= output_channel) {\n" +" for (int i=0; i<4 && (x+i)1\n" +" }\n" +"#endif\n" +"}\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_2d_buf_subgroup_c16_c4_b8(\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __global FLOAT* weights,\n" +" __global FLOAT* biases,\n" +" __private const int pad_width,\n" +" __private const int pad_height,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int output_width,\n" +" __private const int output_height,\n" +" __private const int output_channel,\n" +" __private const int x_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right\n" +") {\n" +" const int sglid=get_sub_group_local_id();\n" +" const int b=(uint)get_global_id(2);\n" +" const int xy=get_global_id(0);\n" +" const int x=(xy % x_blocks) << 3;\n" +" const int y=(xy/x_blocks);\n" +" const int lid1=(int)get_local_id(1);\n" +" const int feature_per_wg=(int)get_local_size(1)/SLM_DIV_FACTOR;\n" +" const int feature_sub_block=lid1/feature_per_wg;\n" +" const int feature_block=(int)get_group_id(1);\n" +" const int input_x=x*STRIDE_WIDTH-pad_width;\n" +" const int input_y=y*STRIDE_HEIGHT-pad_height;\n" +" const uint input_x_pitch=16;\n" +" const uint input_y_pitch=input_x_pitch*(input_pad_left+input_width+input_pad_right);\n" +" const uint input_fs_pitch=input_y_pitch*(input_height);\n" +" const uint input_b_pitch=input_fs_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint input_offset=b*input_b_pitch +\n" +" input_y*input_y_pitch +\n" +" (input_x+input_pad_left)*input_x_pitch;\n" +" const uint output_x_pitch=4;\n" +" const uint output_y_pitch=output_x_pitch*output_width;\n" +" const uint output_fs_pitch=output_y_pitch*output_height;\n" +" const uint output_b_pitch=output_fs_pitch*((output_channel+3)/4);\n" +" const uint output_offset=b*output_b_pitch +\n" +" (feature_block << 2)*output_fs_pitch +\n" +" y*output_y_pitch +\n" +" x*output_x_pitch;\n" +" const uint filter_isv_pitch=16;\n" +" const uint filter_x_pitch=16*16;\n" +" const uint filter_y_pitch=filter_x_pitch*FILTER_WIDTH;\n" +" const uint filter_is_pitch=filter_y_pitch*FILTER_HEIGHT;\n" +" const uint filter_os_pitch=filter_is_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint filter_offset=feature_block*filter_os_pitch;\n" +"#if SLM_DIV_FACTOR == 1\n" +" COMPUTE_FLOAT8 dst=(COMPUTE_FLOAT8)(GROUP_READ(biases,feature_block*16));\n" +"#else\n" +" COMPUTE_FLOAT8 dst;\n" +" if (feature_sub_block == 0) {\n" +" dst=(COMPUTE_FLOAT8)(GROUP_READ(biases,feature_block*16));\n" +" } else {\n" +" dst=(COMPUTE_FLOAT8)0;\n" +" }\n" +"#endif \n" +"#if SLM_DIV_FACTOR>1\n" +" __local COMPUTE_FLOAT8 sum[WORK_GROUP_SIZE];\n" +"#endif\n" +"#if SLM_DIV_FACTOR>1\n" +" for (int icb=feature_sub_block*IC_BLOCKS/SLM_DIV_FACTOR; icb<(feature_sub_block+1)*IC_BLOCKS/SLM_DIV_FACTOR; icb++) {\n" +"#else\n" +" for (int icb=0; icb= input_height)\n" +" continue;\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" {\n" +" int xb=0;\n" +" for (; xb+8 <= INPUT_LINE_SIZE; xb += 8) {\n" +" COMPUTE_FLOAT8 tmp=CONVERT_COMPUTE_FLOAT8(GROUP_READ8(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" line_cache[xb+4]=tmp[4];\n" +" line_cache[xb+5]=tmp[5];\n" +" line_cache[xb+6]=tmp[6];\n" +" line_cache[xb+7]=tmp[7];\n" +" }\n" +" for (; xb+4 <= INPUT_LINE_SIZE; xb += 4) {\n" +" COMPUTE_FLOAT4 tmp=CONVERT_COMPUTE_FLOAT4(GROUP_READ4(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" }\n" +" for (; xb1\n" +" sum[lid1]=dst;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" if (feature_sub_block == 0) {\n" +" __attribute__((opencl_unroll_hint)) for(int i=1; i= output_channel) {\n" +" for (int i=0; i<8 && (x+i)1\n" +" }\n" +"#endif\n" +"}\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_2d_buf_subgroup_c16_c16_b2(\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __global FLOAT* weights,\n" +" __global FLOAT* biases,\n" +" __private const int pad_width,\n" +" __private const int pad_height,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int output_width,\n" +" __private const int output_height,\n" +" __private const int output_channel,\n" +" __private const int x_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right\n" +") {\n" +" const int sglid=get_sub_group_local_id();\n" +" const int b=(uint)get_global_id(2);\n" +" const int xy=get_global_id(0);\n" +" const int x=(xy % x_blocks) << 1;\n" +" const int y=(xy/x_blocks);\n" +" const int lid1=(int)get_local_id(1);\n" +" const int feature_per_wg=(int)get_local_size(1)/SLM_DIV_FACTOR;\n" +" const int feature_sub_block=lid1/feature_per_wg;\n" +" const int feature_block=(int)get_group_id(1);\n" +" const int input_x=x*STRIDE_WIDTH-pad_width;\n" +" const int input_y=y*STRIDE_HEIGHT-pad_height;\n" +" const uint input_x_pitch=16;\n" +" const uint input_y_pitch=input_x_pitch*(input_pad_left+input_width+input_pad_right);\n" +" const uint input_fs_pitch=input_y_pitch*(input_height);\n" +" const uint input_b_pitch=input_fs_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint input_offset=b*input_b_pitch +\n" +" input_y*input_y_pitch +\n" +" (input_x+input_pad_left)*input_x_pitch;\n" +" const uint output_x_pitch=16;\n" +" const uint output_y_pitch=output_x_pitch*(output_pad_left+output_width+output_pad_right);\n" +" const uint output_fs_pitch=output_y_pitch*output_height;\n" +" const uint output_b_pitch=output_fs_pitch*((output_channel+15)/16);\n" +" const uint output_offset=b*output_b_pitch +\n" +" feature_block*output_fs_pitch +\n" +" y*output_y_pitch +\n" +" (x+output_pad_left)*output_x_pitch;\n" +" const uint filter_isv_pitch=16;\n" +" const uint filter_x_pitch=16*16;\n" +" const uint filter_y_pitch=filter_x_pitch*FILTER_WIDTH;\n" +" const uint filter_is_pitch=filter_y_pitch*FILTER_HEIGHT;\n" +" const uint filter_os_pitch=filter_is_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint filter_offset=feature_block*filter_os_pitch;\n" +"#if SLM_DIV_FACTOR == 1\n" +" COMPUTE_FLOAT2 dst=(COMPUTE_FLOAT2)(GROUP_READ(biases,feature_block*16));\n" +"#else\n" +" COMPUTE_FLOAT2 dst;\n" +" if (feature_sub_block == 0) {\n" +" dst=(COMPUTE_FLOAT2)(GROUP_READ(biases,feature_block*16));\n" +" } else {\n" +" dst=(COMPUTE_FLOAT2)0;\n" +" }\n" +"#endif \n" +"#if SLM_DIV_FACTOR>1\n" +" __local COMPUTE_FLOAT2 sum[WORK_GROUP_SIZE];\n" +"#endif\n" +"#if SLM_DIV_FACTOR>1\n" +" for (int icb=feature_sub_block*IC_BLOCKS/SLM_DIV_FACTOR; icb<(feature_sub_block+1)*IC_BLOCKS/SLM_DIV_FACTOR; icb++) {\n" +"#else\n" +" for (int icb=0; icb= input_height)\n" +" continue;\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" {\n" +" int xb=0;\n" +" for (; xb+8 <= INPUT_LINE_SIZE; xb += 8) {\n" +" COMPUTE_FLOAT8 tmp=CONVERT_COMPUTE_FLOAT8(GROUP_READ8(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" line_cache[xb+4]=tmp[4];\n" +" line_cache[xb+5]=tmp[5];\n" +" line_cache[xb+6]=tmp[6];\n" +" line_cache[xb+7]=tmp[7];\n" +" }\n" +" for (; xb+4 <= INPUT_LINE_SIZE; xb += 4) {\n" +" COMPUTE_FLOAT4 tmp=CONVERT_COMPUTE_FLOAT4(GROUP_READ4(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" }\n" +" for (; xb1\n" +" sum[lid1]=dst;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" if (feature_sub_block == 0) {\n" +" __attribute__((opencl_unroll_hint)) for(int i=1; i= output_channel) {\n" +" for (int i=0; i<2; i++) {\n" +" if ((feature_block*16+sglid1\n" +" }\n" +"#endif\n" +"}\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_2d_buf_subgroup_c16_c16_b4(\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __global FLOAT* weights,\n" +" __global FLOAT* biases,\n" +" __private const int pad_width,\n" +" __private const int pad_height,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int output_width,\n" +" __private const int output_height,\n" +" __private const int output_channel,\n" +" __private const int x_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right\n" +") {\n" +" const int sglid=get_sub_group_local_id();\n" +" const int b=(uint)get_global_id(2);\n" +" const int xy=get_global_id(0);\n" +" const int x=(xy % x_blocks) << 2;\n" +" const int y=(xy/x_blocks);\n" +" const int lid1=(int)get_local_id(1);\n" +" const int feature_per_wg=(int)get_local_size(1)/SLM_DIV_FACTOR;\n" +" const int feature_sub_block=lid1/feature_per_wg;\n" +" const int feature_block=(int)get_group_id(1);\n" +" const int input_x=x*STRIDE_WIDTH-pad_width;\n" +" const int input_y=y*STRIDE_HEIGHT-pad_height;\n" +" const uint input_x_pitch=16;\n" +" const uint input_y_pitch=input_x_pitch*(input_pad_left+input_width+input_pad_right);\n" +" const uint input_fs_pitch=input_y_pitch*(input_height);\n" +" const uint input_b_pitch=input_fs_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint input_offset=b*input_b_pitch +\n" +" input_y*input_y_pitch +\n" +" (input_x+input_pad_left)*input_x_pitch;\n" +" const uint output_x_pitch=16;\n" +" const uint output_y_pitch=output_x_pitch*(output_pad_left+output_width+output_pad_right);\n" +" const uint output_fs_pitch=output_y_pitch*output_height;\n" +" const uint output_b_pitch=output_fs_pitch*((output_channel+15)/16);\n" +" const uint output_offset=b*output_b_pitch +\n" +" feature_block*output_fs_pitch +\n" +" y*output_y_pitch +\n" +" (x+output_pad_left)*output_x_pitch;\n" +" const uint filter_isv_pitch=16;\n" +" const uint filter_x_pitch=16*16;\n" +" const uint filter_y_pitch=filter_x_pitch*FILTER_WIDTH;\n" +" const uint filter_is_pitch=filter_y_pitch*FILTER_HEIGHT;\n" +" const uint filter_os_pitch=filter_is_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint filter_offset=feature_block*filter_os_pitch;\n" +"#if SLM_DIV_FACTOR == 1\n" +" COMPUTE_FLOAT4 dst=(COMPUTE_FLOAT4)(GROUP_READ(biases,feature_block*16));\n" +"#else\n" +" COMPUTE_FLOAT4 dst;\n" +" if (feature_sub_block == 0) {\n" +" dst=(COMPUTE_FLOAT4)(GROUP_READ(biases,feature_block*16));\n" +" } else {\n" +" dst=(COMPUTE_FLOAT4)0;\n" +" }\n" +"#endif \n" +"#if SLM_DIV_FACTOR>1\n" +" __local COMPUTE_FLOAT4 sum[WORK_GROUP_SIZE];\n" +"#endif\n" +"#if SLM_DIV_FACTOR>1\n" +" for (int icb=feature_sub_block*IC_BLOCKS/SLM_DIV_FACTOR; icb<(feature_sub_block+1)*IC_BLOCKS/SLM_DIV_FACTOR; icb++) {\n" +"#else\n" +" for (int icb=0; icb= input_height)\n" +" continue;\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" {\n" +" int xb=0;\n" +" for (; xb+8 <= INPUT_LINE_SIZE; xb += 8) {\n" +" COMPUTE_FLOAT8 tmp=CONVERT_COMPUTE_FLOAT8(GROUP_READ8(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" line_cache[xb+4]=tmp[4];\n" +" line_cache[xb+5]=tmp[5];\n" +" line_cache[xb+6]=tmp[6];\n" +" line_cache[xb+7]=tmp[7];\n" +" }\n" +" for (; xb+4 <= INPUT_LINE_SIZE; xb += 4) {\n" +" COMPUTE_FLOAT4 tmp=CONVERT_COMPUTE_FLOAT4(GROUP_READ4(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" }\n" +" for (; xb1\n" +" sum[lid1]=dst;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" if (feature_sub_block == 0) {\n" +" __attribute__((opencl_unroll_hint)) for(int i=1; i= output_channel) {\n" +" for (int i=0; i<4; i++) {\n" +" if ((feature_block*16+sglid1\n" +" }\n" +"#endif\n" +"}\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_2d_buf_subgroup_c16_c16_b8(\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __global FLOAT* weights,\n" +" __global FLOAT* biases,\n" +" __private const int pad_width,\n" +" __private const int pad_height,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int output_width,\n" +" __private const int output_height,\n" +" __private const int output_channel,\n" +" __private const int x_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right,\n" +" __private const int output_pad_left,\n" +" __private const int output_pad_right\n" +") {\n" +" const int sglid=get_sub_group_local_id();\n" +" const int b=(uint)get_global_id(2);\n" +" const int xy=get_global_id(0);\n" +" const int x=(xy % x_blocks) << 3;\n" +" const int y=(xy/x_blocks);\n" +" const int lid1=(int)get_local_id(1);\n" +" const int feature_per_wg=(int)get_local_size(1)/SLM_DIV_FACTOR;\n" +" const int feature_sub_block=lid1/feature_per_wg;\n" +" const int feature_block=(int)get_group_id(1);\n" +" const int input_x=x*STRIDE_WIDTH-pad_width;\n" +" const int input_y=y*STRIDE_HEIGHT-pad_height;\n" +" const uint input_x_pitch=16;\n" +" const uint input_y_pitch=input_x_pitch*(input_pad_left+input_width+input_pad_right);\n" +" const uint input_fs_pitch=input_y_pitch*(input_height);\n" +" const uint input_b_pitch=input_fs_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint input_offset=b*input_b_pitch +\n" +" input_y*input_y_pitch +\n" +" (input_x+input_pad_left)*input_x_pitch;\n" +" const uint output_x_pitch=16;\n" +" const uint output_y_pitch=output_x_pitch*(output_pad_left+output_width+output_pad_right);\n" +" const uint output_fs_pitch=output_y_pitch*output_height;\n" +" const uint output_b_pitch=output_fs_pitch*((output_channel+15)/16);\n" +" const uint output_offset=b*output_b_pitch +\n" +" feature_block*output_fs_pitch +\n" +" y*output_y_pitch +\n" +" (x+output_pad_left)*output_x_pitch;\n" +" const uint filter_isv_pitch=16;\n" +" const uint filter_x_pitch=16*16;\n" +" const uint filter_y_pitch=filter_x_pitch*FILTER_WIDTH;\n" +" const uint filter_is_pitch=filter_y_pitch*FILTER_HEIGHT;\n" +" const uint filter_os_pitch=filter_is_pitch*((INPUT_CHANNEL+15)/16);\n" +" const uint filter_offset=feature_block*filter_os_pitch;\n" +"#if SLM_DIV_FACTOR == 1\n" +" COMPUTE_FLOAT8 dst=(COMPUTE_FLOAT8)(GROUP_READ(biases,feature_block*16));\n" +"#else\n" +" COMPUTE_FLOAT8 dst;\n" +" if (feature_sub_block == 0) {\n" +" dst=(COMPUTE_FLOAT8)(GROUP_READ(biases,feature_block*16));\n" +" } else {\n" +" dst=(COMPUTE_FLOAT8)0;\n" +" }\n" +"#endif \n" +"#if SLM_DIV_FACTOR>1\n" +" __local COMPUTE_FLOAT8 sum[WORK_GROUP_SIZE];\n" +"#endif\n" +"#if SLM_DIV_FACTOR>1\n" +" for (int icb=feature_sub_block*IC_BLOCKS/SLM_DIV_FACTOR; icb<(feature_sub_block+1)*IC_BLOCKS/SLM_DIV_FACTOR; icb++) {\n" +"#else\n" +" for (int icb=0; icb= input_height)\n" +" continue;\n" +" FLOAT line_cache[INPUT_LINE_SIZE];\n" +" {\n" +" int xb=0;\n" +" for (; xb+8 <= INPUT_LINE_SIZE; xb += 8) {\n" +" COMPUTE_FLOAT8 tmp=CONVERT_COMPUTE_FLOAT8(GROUP_READ8(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" line_cache[xb+4]=tmp[4];\n" +" line_cache[xb+5]=tmp[5];\n" +" line_cache[xb+6]=tmp[6];\n" +" line_cache[xb+7]=tmp[7];\n" +" }\n" +" for (; xb+4 <= INPUT_LINE_SIZE; xb += 4) {\n" +" COMPUTE_FLOAT4 tmp=CONVERT_COMPUTE_FLOAT4(GROUP_READ4(input,input_offset +\n" +" icb*input_fs_pitch +\n" +" kh*DILATION_HEIGHT*input_y_pitch +\n" +" xb*input_x_pitch));\n" +" \n" +" line_cache[xb+0]=tmp[0];\n" +" line_cache[xb+1]=tmp[1];\n" +" line_cache[xb+2]=tmp[2];\n" +" line_cache[xb+3]=tmp[3];\n" +" }\n" +" for (; xb1\n" +" sum[lid1]=dst;\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" if (feature_sub_block == 0) {\n" +" __attribute__((opencl_unroll_hint)) for(int i=1; i= output_channel) {\n" +" for (int i=0; i<8; i++) {\n" +" if ((feature_block*16+sglid1\n" +" }\n" +"#endif\n" +"}\n" +; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* input_transe_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__attribute__((intel_reqd_sub_group_size(16)))\n" +"__kernel void conv_transe_c4_c1(\n" +" int global_size_dim0,\n" +" int global_size_dim1,\n" +" int global_size_dim2,\n" +" __global FLOAT* input,\n" +" __global FLOAT* output,\n" +" __private const int input_width,\n" +" __private const int input_height,\n" +" __private const int input_channel,\n" +" __private const int channel_blocks,\n" +" __private const int input_pad_left,\n" +" __private const int input_pad_right)\n" +"{\n" +" int x=get_global_id(0);\n" +" int w=x % input_width;\n" +" int h=x/input_width;\n" +" int c=get_global_id(1);\n" +" int b=get_global_id(2);\n" +" int cout=c << 2;\n" +" if(x >= global_size_dim0 || c >= global_size_dim1 || b >= global_size_dim2)\n" +" return;\n" +" // Input offset calculations:\n" +" const uint input_x_pitch=4;\n" +" const uint input_y_pitch=input_x_pitch*input_width;\n" +" const uint input_f_pitch=input_y_pitch*input_height;\n" +" const uint input_b_pitch=input_f_pitch*channel_blocks;\n" +" const uint input_offset=b*input_b_pitch +\n" +" c*input_f_pitch +\n" +" h*input_y_pitch +\n" +" w*input_x_pitch;\n" +" // Output offset calculations:\n" +" const uint output_x_pitch=1;\n" +" const uint output_y_pitch=output_x_pitch*input_width;\n" +" const uint output_f_pitch=output_y_pitch*input_height;\n" +" const uint output_b_pitch=output_f_pitch*input_channel;\n" +" const uint output_offset=b*output_b_pitch +\n" +" cout*output_f_pitch+\n" +" h*output_y_pitch +\n" +" w*output_x_pitch;\n" +" \n" +" FLOAT4 value=vload4(0,input+input_offset);\n" +" for(int i=0; i<4 && cout+i> 2;\n" +" if(x >= global_size_dim0 || c >= global_size_dim1 || b >= global_size_dim2)\n" +" return;\n" +" \n" +" // Input offset calculations:\n" +" const uint input_x_pitch=4;\n" +" const uint input_y_pitch=input_x_pitch*input_width;\n" +" const uint input_f_pitch=input_y_pitch*input_height;\n" +" const uint input_b_pitch=input_f_pitch*channel_blocks;\n" +" \n" +" const uint input_offset=b*input_b_pitch +\n" +" c*input_f_pitch +\n" +" h*input_y_pitch +\n" +" w*input_x_pitch;\n" +" \n" +" // Output offset calculations:\n" +" const uint output_x_pitch=16;\n" +" const uint output_y_pitch=output_x_pitch*(input_pad_left+input_width+input_pad_right);\n" +" const uint output_f_pitch=output_y_pitch*input_height;\n" +" const uint output_b_pitch=output_f_pitch*((input_channel+15)/16);\n" +" \n" +" const uint output_offset=b*output_b_pitch +\n" +" cout*output_f_pitch+\n" +" h*output_y_pitch +\n" +" (w+input_pad_left)*output_x_pitch+(c % 4)*4;\n" +" \n" +" FLOAT4 value=vload4(0,input+input_offset);\n" +" vstore4(value,0,output+output_offset);\n" +" if(w == 0){\n" +" uint pad_offset=b*output_b_pitch+cout*output_f_pitch+h*output_y_pitch+(c % 4)*4;\n" +" for(int i=0; i= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void reduct_width_buf(GLOBAL_SIZE_3_DIMS\n" +" __global const INPUT_TYPE* input,\n" +" __global OUTPUT_TYPE* output,\n" +" __private const int inputWidth,\n" +" __private const int inputHeight,\n" +" __private const int inputChannel,\n" +" __private const int inputBatch,\n" +" __private const int inputChannelBlock,\n" +" __private const int oututWidth,\n" +" __private const int outputHeight,\n" +" __private const int outputChannel,\n" +" __private const int outputChannelBlock\n" +" ) {\n" +" const int width_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/outputChannelBlock;\n" +" const int channel_idx=batch_channel_idx % outputChannelBlock;\n" +" const int offset=((((batch_idx*inputChannelBlock)+channel_idx)*inputHeight+height_idx)*inputWidth+0)*4;\n" +" const int outputOffset=((((batch_idx*outputChannelBlock)+channel_idx)*outputHeight+height_idx)*oututWidth+0)*4;\n" +" INPUT_TYPE4 out=(INPUT_TYPE4)VALUE;\n" +" \n" +"#if LOCAL_SIZE>0\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE4 local sum[LOCAL_SIZE];\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int width_idx=get_group_id(0);\n" +" const int batch_idx=batch_channel_idx/outputChannelBlock;\n" +" const int channel_idx=batch_channel_idx % outputChannelBlock;\n" +" \n" +" const int offset=((((batch_idx*inputChannelBlock)+channel_idx)*inputHeight+0)*inputWidth+width_idx)*4;\n" +" const int outputOffset=((((batch_idx*outputChannelBlock)+channel_idx)*outputHeight+0)*oututWidth+width_idx)*4;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE4 local sum[LOCAL_SIZE];\n" +" INPUT_TYPE4 out=(INPUT_TYPE4)VALUE;\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_idx=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,batch_idx);\n" +" const int width_idx=get_group_id(0);\n" +" \n" +" const int offset=((((batch_idx*inputChannelBlock)+0)*inputHeight+height_idx)*inputWidth+width_idx)*4;\n" +" const int outputOffset=((((batch_idx*outputChannelBlock)+0)*outputHeight+height_idx)*oututWidth+width_idx)*4;\n" +" int remain=inputChannel-(inputChannelBlock-1)*4;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE local sum[LOCAL_SIZE];\n" +" INPUT_TYPE4 out=(INPUT_TYPE4)VALUE;\n" +" INPUT_TYPE4 in;\n" +" INPUT_TYPE *inPtr=(INPUT_TYPE*)∈\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_idx=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,batch_idx);\n" +" const int width_idx=get_group_id(0);\n" +" \n" +" const int offset=((((batch_idx*inputChannelBlock)+0)*inputHeight+height_idx)*inputWidth+width_idx)*4;\n" +" const int outputOffset=((batch_idx*outputHeight+height_idx)*oututWidth+width_idx);\n" +" int remain=inputChannel-(inputChannelBlock-1)*4;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE local sum[LOCAL_SIZE];\n" +" INPUT_TYPE4 out=(INPUT_TYPE4)VALUE;\n" +" INPUT_TYPE4 in;\n" +" INPUT_TYPE *inPtr=(INPUT_TYPE*)∈\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,channel_idx);\n" +" const int width_idx=get_group_id(0);\n" +" \n" +" const int offset=((((0*inputChannelBlock)+channel_idx)*inputHeight+height_idx)*inputWidth+width_idx)*4;\n" +" const int outputOffset=((((0*outputChannelBlock)+channel_idx)*outputHeight+height_idx)*oututWidth+width_idx)*4;\n" +" int batchOffset=inputChannelBlock*inputHeight*inputWidth;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE4 local sum[LOCAL_SIZE];\n" +" INPUT_TYPE4 out=(INPUT_TYPE4)VALUE;\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid local (matrix A)\n" +" #if SA == 1\n" +" GlobalToLocalA(agm,alm,kSizeM,tid,kwg);\n" +" #endif\n" +" // Loads data: off-chip --> local (matrix B)\n" +" #if SB == 1\n" +" GlobalToLocalB(bgm,blm,kSizeN,tid,kwg);\n" +" #endif\n" +" #if SA == 1 || SB == 1\n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" #endif\n" +" // Loops over all workitem tiles,unrolled by a factor KWI\n" +" for (int pwi=0; pwi private (matrix A)\n" +" #if GEMMK == 0 && SA == 1\n" +" apm[_mi]=LocalToPrivateA(alm,_mi,kg);\n" +" // Loads data: off-chip --> private (matrix A)\n" +" #elif GEMMK == 0 && SA == 0\n" +" apm[_mi]=GlobalToPrivateA(agm,_mi,kSizeM,idk,kwg);\n" +" #endif\n" +" }\n" +" // Loads matrix B (kernel 0) or matrix A (kernel 1)\n" +" #pragma unroll\n" +" for (int _ni=0; _ni private (matrix B)\n" +" #if SB == 1\n" +" bpm[_ni]=LocalToPrivateB(blm,_ni,kg);\n" +" // Loads data: off-chip --> private (matrix B)\n" +" #else\n" +" bpm[_ni]=GlobalToPrivateB(bgm,_ni,kSizeN,idk);\n" +" #endif\n" +" }\n" +" // Performs the accumulation (Cpm += Apm*Bpm)\n" +" #ifdef OUTPUTMN\n" +" #pragma unroll\n" +" for (int _mi=0; _mi= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void cast(GLOBAL_SIZE_3_DIMS\n" +" __read_only image2d_t input,\n" +" __write_only image2d_t output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channelBlock\n" +" ) {\n" +" const int width_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/channelBlock;\n" +" const int channel_idx=batch_channel_idx % channelBlock;\n" +" \n" +"#ifdef TO_BOOL\n" +" int4 value=convert_int4(RI_DATA(input,SAMPLER,(int2)(channel_idx*width+width_idx,batch_idx*height+height_idx)));\n" +" value=value == (int4)0 ? (int4)0 : (int4)1;\n" +" WI_DATA(output,(int2)(channel_idx*width+width_idx,batch_idx*height+height_idx),CONVERT_OUTPUT_I4(value));\n" +"#else\n" +" INPUT_TYPE_I4 value=RI_DATA(input,SAMPLER,(int2)(channel_idx*width+width_idx,batch_idx*height+height_idx));\n" +" WI_DATA(output,(int2)(channel_idx*width+width_idx,batch_idx*height+height_idx),CONVERT_OUTPUT_I4(value));\n" +"#endif\n" +"}\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* buffer_convert_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"// convert data from buffer(nhwc) to buffer(nc4hw4)\n" +"__kernel void nhwc_buffer_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int height,\n" +" __private const int width,__private const int channels,\n" +" __global OUTPUT_TYPE *output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_4_idx=(image_width_idx/width) << 2;\n" +" const int buffer_offset=((batch_idx*height+height_idx)*width+width_idx)*channels+channel_4_idx;\n" +" const int remain_channel=channels-channel_4_idx;\n" +" float4 values=convert_float4(vload4(0,input_ptr+buffer_offset));\n" +" if (remain_channel == 3) {\n" +" values.w=0;\n" +" } else if (remain_channel == 2) {\n" +" values.z=0;\n" +" values.w=0;\n" +" } else if (remain_channel == 1) {\n" +" values.y=0;\n" +" values.z=0;\n" +" values.w=0;\n" +" }\n" +" const int out_offset=(((batch_idx*((channels+3)/4)+channel_4_idx/4)*height+height_idx)*width+width_idx)*4;\n" +" vstore4(CONVERT_OUTPUT4(values),0,output+out_offset);\n" +"}\n" +"// convert data from buffer(nchw) to buffer(nc4hw4)\n" +"__kernel void nchw_buffer_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int height,__private const int width,__private const int channels,\n" +" __global OUTPUT_TYPE *output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_4_idx=image_width_idx/width << 2;\n" +" const int buffer_offset=((batch_idx*channels+channel_4_idx)*height+height_idx)*width+width_idx;\n" +" const int remain_channel=channels-channel_4_idx;\n" +" const int height_width_size=height*width;\n" +" float4 output_values=0;\n" +" if (remain_channel >= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(float)*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.y=(float)*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.z=(float)*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.w=(float)*(input_ptr+offset);\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(float)*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.y=(float)*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.z=(float)*(input_ptr+offset);\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(float)*(input_ptr+offset);\n" +" offset += height_width_size;\n" +" output_values.y=(float)*(input_ptr+offset);\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(float)*(input_ptr+offset);\n" +" }\n" +" const int out_offset=(((batch_idx*((channels+3)/4)+channel_4_idx/4)*height+height_idx)*width+width_idx)*4;\n" +" vstore4(CONVERT_OUTPUT4(output_values),0,output+out_offset);\n" +"}\n" +"__kernel void nchw_buffer_to_nchw_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global INPUT_TYPE *input_ptr,\n" +" __private const int height,__private const int width,__private const int channels,\n" +" __private const int input_pad_left,__private const int input_pad_right,\n" +" __private const int output_pad_left,__private const int output_pad_right,\n" +" __global OUTPUT_TYPE *output) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int src_width=width+input_pad_left+input_pad_right;\n" +" const int dst_width=width+output_pad_left+output_pad_right;\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_idx=image_width_idx/width;\n" +" const int in_offset=((batch_idx*channels+channel_idx)*height+height_idx)*src_width+width_idx+input_pad_left;\n" +" const int out_offset=((batch_idx*channels+channel_idx)*height+height_idx)*dst_width+width_idx+output_pad_left;\n" +" output[out_offset]=(OUTPUT_TYPE)input_ptr[in_offset];\n" +"}\n" +"// convert data from image(b h,ic/4 w ic4) to buffer(nhwc)\n" +"__kernel void nc4hw4_buffer_to_nhwc_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int height,__private const int width,\n" +" __private const int channels,\n" +" __global INPUT_TYPE *input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" const int channel_4_idx=(image_width_idx/width) << 2;\n" +" const int buffer_offset=((batch_idx*height+height_idx)*width+width_idx)*channels+channel_4_idx;\n" +" const int in_offset=(((batch_idx*((channels+3)/4)+channel_4_idx/4)*height+height_idx)*width+width_idx)*4;\n" +" \n" +" float4 values=convert_float4(vload4(0,input_ptr+in_offset));\n" +" const int remain_channel=channels-channel_4_idx;\n" +" if (remain_channel >= 4) {\n" +" vstore4(CONVERT_OUTPUT4(values),0,output+buffer_offset);\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset++;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" }\n" +"}\n" +"// convert data from buffer(nc4hw4) to buffer(nchw)\n" +"__kernel void nc4hw4_buffer_to_nchw_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global OUTPUT_TYPE *output,\n" +" __private const int height,__private const int width,\n" +" __private const int channels,\n" +" __global INPUT_TYPE *input_ptr) {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" \n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/height;\n" +" const int height_idx=image_height_idx % height;\n" +" const int width_idx=image_width_idx % width;\n" +" int channel_4_idx=(image_width_idx/width)*4;\n" +" int buffer_offset=((batch_idx*channels+channel_4_idx)*height+height_idx)*width+width_idx;\n" +" \n" +" const int in_offset=(((batch_idx*((channels+3)/4)+channel_4_idx/4)*height+height_idx)*width+width_idx)*4;\n" +" float4 values=convert_float4(vload4(0,input_ptr+in_offset));\n" +" const int height_width_size=height*width;\n" +" const int remain_channel=channels-channel_4_idx;\n" +" if (remain_channel >= 4) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.w;\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.z;\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" offset += height_width_size;\n" +" output[offset]=(OUTPUT_TYPE)values.y;\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output[offset]=(OUTPUT_TYPE)values.x;\n" +" }\n" +"}\n" +"__kernel void nc4hw4_buffer_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const INPUT_TYPE *input_ptr,\n" +" __private const int2 output_shape,\n" +" __private const int2 src_stride,\n" +" __private const int2 dst_stride,\n" +" __global OUTPUT_TYPE *output\n" +") {\n" +" int image_width_idx=get_global_id(0);\n" +" int image_height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int batch_idx=image_height_idx/output_shape.x;\n" +" const int height_idx=image_height_idx % output_shape.x;\n" +" const int width_idx=image_width_idx % output_shape.y;\n" +" const int channel_block_idx=image_width_idx/output_shape.y;\n" +" int2 src_bc_offset=src_stride*(int2)(batch_idx,channel_block_idx);\n" +" int2 dst_bc_offset=dst_stride*(int2)(batch_idx,channel_block_idx);\n" +" int src_buffer_offset =\n" +" (((src_bc_offset.x+src_bc_offset.y)*output_shape.x+height_idx)*output_shape.y+width_idx)*4;\n" +" int dst_buffer_offset =\n" +" (((dst_bc_offset.x+dst_bc_offset.y)*output_shape.x+height_idx)*output_shape.y+width_idx)*4;\n" +" \n" +" vstore4(CONVERT_OUTPUT4(vload4(0,input_ptr+src_buffer_offset)),0,output+dst_buffer_offset);\n" +"}\n" +"// convert kernel : from buffer(oihw) to image(oc/4 h w ,ic oc4)\n" +"__kernel void conv2d_filter_buffer_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input_ptr,\n" +" __private const int output_channel,\n" +" __private const int2 kernel_shape,\n" +" __private const int ic_h_w_size,\n" +" __private const int height_width_size,\n" +" __global FLOAT *output) {\n" +" int image_width_idx=get_global_id(0); // ic\n" +" int image_height_idx=get_global_id(1); // oc/4 h w\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int input_channel_4_idx=image_width_idx;\n" +" const int output_channel_4_idx=(image_height_idx/height_width_size)*4;\n" +" const int height_width_idx=image_height_idx % height_width_size;\n" +" const int buffer_height_idx=height_width_idx/kernel_shape.y;\n" +" const int buffer_width_idx=height_width_idx % kernel_shape.y;\n" +" const int buffer_offset=output_channel_4_idx*ic_h_w_size+input_channel_4_idx*height_width_size +\n" +" buffer_height_idx*kernel_shape.y+buffer_width_idx;\n" +" FLOAT4 output_values=0;\n" +" if (output_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.w=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" const int out_offset=(image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*4;\n" +" vstore4(output_values,0,output+out_offset);\n" +"}\n" +"// convert kernel : from buffer(oihw) to image(oc/4 h w ,ic oc4)\n" +"__kernel void conv2d_filter_buffer_to_nc4hw4_buffer_floatin(GLOBAL_SIZE_2_DIMS\n" +" __global const float *input_ptr,\n" +" __private const int output_channel,\n" +" __private const int2 kernel_shape,\n" +" __private const int ic_h_w_size,\n" +" __private const int height_width_size,\n" +" __global FLOAT *output) {\n" +" int image_width_idx=get_global_id(0); // ic\n" +" int image_height_idx=get_global_id(1); // oc/4 h w\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" const int input_channel_4_idx=image_width_idx;\n" +" const int output_channel_4_idx=(image_height_idx/height_width_size)*4;\n" +" const int height_width_idx=image_height_idx % height_width_size;\n" +" const int buffer_height_idx=height_width_idx/kernel_shape.y;\n" +" const int buffer_width_idx=height_width_idx % kernel_shape.y;\n" +" const int buffer_offset=output_channel_4_idx*ic_h_w_size+input_channel_4_idx*height_width_size +\n" +" buffer_height_idx*kernel_shape.y+buffer_width_idx;\n" +" FLOAT4 output_values=0;\n" +" if (output_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.w=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += ic_h_w_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset=mad24(1,ic_h_w_size,offset);\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" const int out_offset=(image_width_idx*height_width_size*((output_channel+3)/4)+image_height_idx)*4;\n" +" vstore4(output_values,0,output+out_offset);\n" +"}\n" +"// convert kernel from buffer(mihw) to image(ic/4,ic4 h w m)\n" +"// but now dw only support m == 1\n" +"__kernel void dw_filter_buffer_to_nc4hw4_buffer(GLOBAL_SIZE_2_DIMS\n" +" __global const FLOAT *input_ptr,\n" +" __private const int4 kernel_shape,//[1,Cout,fh,fw]\n" +" __private const int height_width_size,\n" +" __global FLOAT *output) {\n" +" const int image_width_idx=get_global_id(0);//fh*fw\n" +" const int image_height_idx=get_global_id(1);//UP_DIV(Cout,4)\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" FLOAT4 output_values=0;\n" +" if (kernel_shape.x == 1) {\n" +" const int input_channel_4_idx=image_height_idx*4;\n" +" const int buffer_height_idx=image_width_idx/kernel_shape.w;\n" +" const int buffer_width_idx=image_width_idx % kernel_shape.w;\n" +" const int buffer_offset =\n" +" mad24(mad24(input_channel_4_idx,kernel_shape.z,buffer_height_idx),kernel_shape.w,buffer_width_idx);\n" +" //input [1,Cout,fh,fw]\n" +" //index:[0,input_channel_4_idx,buffer_height_idx,buffer_width_idx]\n" +" const int remain_channel=kernel_shape.y-input_channel_4_idx;\n" +" if (input_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.w=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" }\n" +" //output NC4HW4 [1,fw*fh,1,Cout/4]x oc4\n" +" //index: [0,image_width_idx,0,image_height_idx]\n" +" const int out_offset=(image_width_idx*((kernel_shape.y+3)/4)+image_height_idx)*4;\n" +" vstore4(output_values,0,output+out_offset);\n" +"}\n" +"__kernel void dw_filter_buffer_to_nc4hw4_buffer_floatin(GLOBAL_SIZE_2_DIMS\n" +" __global const float *input_ptr,\n" +" __private const int4 kernel_shape,//[1,Cout,fh,fw]\n" +" __private const int height_width_size,\n" +" __global FLOAT *output) {\n" +" const int image_width_idx=get_global_id(0);//fh*fw\n" +" const int image_height_idx=get_global_id(1);//UP_DIV(Cout,4)\n" +" DEAL_NON_UNIFORM_DIM2(image_width_idx,image_height_idx);\n" +" FLOAT4 output_values=0;\n" +" if (kernel_shape.x == 1) {\n" +" const int input_channel_4_idx=image_height_idx*4;\n" +" const int buffer_height_idx=image_width_idx/kernel_shape.w;\n" +" const int buffer_width_idx=image_width_idx % kernel_shape.w;\n" +" const int buffer_offset =\n" +" mad24(mad24(input_channel_4_idx,kernel_shape.z,buffer_height_idx),kernel_shape.w,buffer_width_idx);\n" +" //input [1,Cout,fh,fw]\n" +" //index:[0,input_channel_4_idx,buffer_height_idx,buffer_width_idx]\n" +" const int remain_channel=kernel_shape.y-input_channel_4_idx;\n" +" if (input_channel_4_idx= 4) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.w=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 3) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.z=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 2) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" offset += height_width_size;\n" +" output_values.y=(FLOAT)(*(input_ptr+offset));\n" +" } else if (remain_channel == 1) {\n" +" int offset=buffer_offset;\n" +" output_values.x=(FLOAT)(*(input_ptr+offset));\n" +" }\n" +" }\n" +" }\n" +" //output NC4HW4 [1,fw*fh,1,Cout/4]x oc4\n" +" //index: [0,image_width_idx,0,image_height_idx]\n" +" const int out_offset=(image_width_idx*((kernel_shape.y+3)/4)+image_height_idx)*4;\n" +" vstore4(output_values,0,output+out_offset);\n" +"}\n" +; +#endif +const char* matmul = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_2_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) ""if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { ""return; ""}\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void matmul(GLOBAL_SIZE_2_DIMS __read_only image2d_t input_a,\n" +" __read_only image2d_t input_b,\n" +" #ifdef BIAS\n" +" __read_only image2d_t input_c,\n" +" #endif\n" +" __write_only image2d_t output_c,__private const int channels,\n" +" __private const int channel_blocks) {\n" +" const int width_blocks_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(width_blocks_idx,height_idx);\n" +" FLOAT4 a;\n" +" FLOAT4 b0=0,b1=0,b2=0,b3=0;\n" +" #ifdef BIAS\n" +" FLOAT4 temp=RI_F(input_c,SAMPLER,(int2)(width_blocks_idx,0));\n" +" FLOAT result0=temp.x;\n" +" FLOAT result1=temp.y;\n" +" FLOAT result2=temp.z;\n" +" FLOAT result3=temp.w;\n" +" #else\n" +" FLOAT result0=0;\n" +" FLOAT result1=0;\n" +" FLOAT result2=0;\n" +" FLOAT result3=0;\n" +" #endif\n" +" for (short pos=0; pos= 1) ? v_zero : a3);\n" +" a2=((remain >= 2) ? v_zero : a2);\n" +" a1=((remain >= 3) ? v_zero : a1);\n" +" FLOAT4 a0_trans=(FLOAT4)(a0.x,a1.x,a2.x,a3.x);\n" +" FLOAT4 a1_trans=(FLOAT4)(a0.y,a1.y,a2.y,a3.y);\n" +" FLOAT4 a2_trans=(FLOAT4)(a0.z,a1.z,a2.z,a3.z);\n" +" FLOAT4 a3_trans=(FLOAT4)(a0.w,a1.w,a2.w,a3.w);\n" +" \n" +" FLOAT4 b0_trans=(FLOAT4)(b0.x,b1.x,b2.x,b3.x);\n" +" FLOAT4 b1_trans=(FLOAT4)(b0.y,b1.y,b2.y,b3.y);\n" +" FLOAT4 b2_trans=(FLOAT4)(b0.z,b1.z,b2.z,b3.z);\n" +" FLOAT4 b3_trans=(FLOAT4)(b0.w,b1.w,b2.w,b3.w);\n" +" //matmul\n" +" result0.x += dot(a0_trans,b0_trans);\n" +" result0.y += dot(a0_trans,b1_trans);\n" +" result0.z += dot(a0_trans,b2_trans);\n" +" result0.w += dot(a0_trans,b3_trans);\n" +" \n" +" result1.x += dot(a1_trans,b0_trans);\n" +" result1.y += dot(a1_trans,b1_trans);\n" +" result1.z += dot(a1_trans,b2_trans);\n" +" result1.w += dot(a1_trans,b3_trans);\n" +" \n" +" result2.x += dot(a2_trans,b0_trans);\n" +" result2.y += dot(a2_trans,b1_trans);\n" +" result2.z += dot(a2_trans,b2_trans);\n" +" result2.w += dot(a2_trans,b3_trans);\n" +" \n" +" result3.x += dot(a3_trans,b0_trans);\n" +" result3.y += dot(a3_trans,b1_trans);\n" +" result3.z += dot(a3_trans,b2_trans);\n" +" result3.w += dot(a3_trans,b3_trans);\n" +" }\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx),result0);\n" +" if(4*height_blocks_idx+1 >= height) return;\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx+1),result1);\n" +" if(4*height_blocks_idx+2 >= height) return;\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx+2),result2);\n" +" if(4*height_blocks_idx+3 >= height) return;\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx+3),result3);\n" +"}\n" +"__kernel void matmul_transA_transB(GLOBAL_SIZE_2_DIMS __read_only image2d_t input_a,\n" +" __read_only image2d_t input_b,\n" +" #ifdef BIAS\n" +" __read_only image2d_t input_c,\n" +" #endif\n" +" __write_only image2d_t output_c,\n" +" __private const int channels,\n" +" __private const int channel_blocks,\n" +" __private const int height) {\n" +" const int width_blocks_idx=get_global_id(0);\n" +" const int height_blocks_idx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(width_blocks_idx,height_blocks_idx);\n" +" FLOAT4 v_zero=(FLOAT4)((FLOAT)0.0);\n" +" #ifdef BIAS\n" +" FLOAT4 result0=RI_F(input_c,SAMPLER,(int2)(width_blocks_idx,0));\n" +" FLOAT4 result1=result0;\n" +" FLOAT4 result2=result0;\n" +" FLOAT4 result3=result0;\n" +" #else\n" +" FLOAT4 result0=0;\n" +" FLOAT4 result1=0;\n" +" FLOAT4 result2=0;\n" +" FLOAT4 result3=0;\n" +" #endif\n" +" for (short pos=0; pos= 1) ? v_zero : a3);\n" +" a2=((remain >= 2) ? v_zero : a2);\n" +" a1=((remain >= 3) ? v_zero : a1);\n" +" FLOAT4 a0_trans=(FLOAT4)(a0.x,a1.x,a2.x,a3.x);\n" +" FLOAT4 a1_trans=(FLOAT4)(a0.y,a1.y,a2.y,a3.y);\n" +" FLOAT4 a2_trans=(FLOAT4)(a0.z,a1.z,a2.z,a3.z);\n" +" FLOAT4 a3_trans=(FLOAT4)(a0.w,a1.w,a2.w,a3.w);\n" +" //matmul\n" +" result0.x += dot(a0_trans,b0);\n" +" result0.y += dot(a0_trans,b1);\n" +" result0.z += dot(a0_trans,b2);\n" +" result0.w += dot(a0_trans,b3);\n" +" \n" +" result1.x += dot(a1_trans,b0);\n" +" result1.y += dot(a1_trans,b1);\n" +" result1.z += dot(a1_trans,b2);\n" +" result1.w += dot(a1_trans,b3);\n" +" \n" +" result2.x += dot(a2_trans,b0);\n" +" result2.y += dot(a2_trans,b1);\n" +" result2.z += dot(a2_trans,b2);\n" +" result2.w += dot(a2_trans,b3);\n" +" \n" +" result3.x += dot(a3_trans,b0);\n" +" result3.y += dot(a3_trans,b1);\n" +" result3.z += dot(a3_trans,b2);\n" +" result3.w += dot(a3_trans,b3);\n" +" }\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx),result0);\n" +" if(4*height_blocks_idx+1 >= height) return;\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx+1),result1);\n" +" if(4*height_blocks_idx+2 >= height) return;\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx+2),result2);\n" +" if(4*height_blocks_idx+3 >= height) return;\n" +" WI_F(output_c,(int2)(width_blocks_idx,4*height_blocks_idx+3),result3);\n" +"}\n" +; +const char* binary = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define PI 3.141592653589f\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void binary(__private int global_dim0,__private int global_dim1,\n" +" __read_only image2d_t input0,__read_only image2d_t input1,\n" +" __write_only image2d_t output,\n" +" __private const int4 shape,//[N,H,W,C4]\n" +" __private const int2 isFull,\n" +" __private const int activationType) {\n" +" int2 pos=(int2)(get_global_id(0),get_global_id(1));//WC4,NH\n" +" \n" +" float4 in0,in1;\n" +" if (pos.x= dim.x && pos.y >= dim.y) {\n" +" return;\n" +" }\n" +" WI_DATA(output,pos,CONVERT_OUTPUT_I4(RI_DATA(input,SAMPLER,pos)));\n" +"}\n" +; +#ifndef MNN_OPENCL_BUFFER_CLOSED +const char* loop_buf = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define PI 3.141592653589f\n" +"#ifndef WGSW\n" +" #define WGSW 32 // work-group handle size W dimension\n" +"#endif\n" +"#ifndef WGSC\n" +" #define WGSC 32 // work-group handle size C dimension\n" +"#endif\n" +"#ifndef WGSH\n" +" #define WGSH 32 // work-group handle size H dimension\n" +"#endif\n" +"#ifndef TSW\n" +" #define TSW 8 // thread handle size W dimension\n" +"#endif\n" +"#ifndef TSC\n" +" #define TSC 8 // thread handle size C dimension\n" +"#endif\n" +"#ifndef TSH\n" +" #define TSH 8 // thread handle size H dimension\n" +"#endif\n" +"// [N C4 H 1 4] -> [N H C 1]\n" +"__kernel void tile_trans_3d_buf(__global INPUT_TYPE* input,\n" +" __global OUTPUT_TYPE* output,\n" +" __private const int widthPad,\n" +" __private const int heightPad,\n" +" __private const int channelPad,\n" +" __private const int batch,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel\n" +") {\n" +" int b=get_global_id(2);\n" +" \n" +" const int lidc=get_local_id(0);\n" +" const int lidh=get_local_id(1);\n" +" // group id\n" +" const int c=get_group_id(0)*WGSC;\n" +" const int h=get_group_id(1)*WGSH;\n" +" const int channel_4=(channel+3) >> 2;\n" +" int jc=lidc;\n" +" int ih=lidh;\n" +" \n" +" __local INPUT_TYPE4 localData[WGSH][WGSC/4];//h64c64\n" +" \n" +" #pragma unroll\n" +" for(int i=0; i= height || c+4*offset_c >= channel) ? (INPUT_TYPE4)0 : vload4(0,input+((b*channel_4+(c/4+offset_c))*height+(h+offset_h))*4);\n" +" }\n" +" }\n" +" \n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" \n" +" // C offset: [WGSC/TSC,TSC/4]\n" +" // H offset: [WGSH/TSH,TSH]\n" +" int oc_base=jc*TSC/4;\n" +" int oh_base=ih*TSH;\n" +" //#pragma unroll\n" +" for(int i=0; i [N C W H]\n" +"__kernel void tile_trans_4d_buf(__global INPUT_TYPE* input,\n" +" __global OUTPUT_TYPE* output,\n" +" __private const int widthPad,\n" +" __private const int heightPad,\n" +" __private const int channelPad,\n" +" __private const int batch,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel\n" +") {\n" +" int bc=get_global_id(2);\n" +" int b=bc % batch;\n" +" int c4=bc/batch;\n" +" int c=c4 << 2;\n" +" \n" +" const int lidw=get_local_id(0);\n" +" const int lidh=get_local_id(1);\n" +" // group id\n" +" const int w=get_group_id(0)*WGSW;\n" +" const int h=get_group_id(1)*WGSH;\n" +" const int channel_4=(channel+3) >> 2;\n" +" int jw=lidw;\n" +" int ih=lidh;\n" +" \n" +" __local INPUT_TYPE4 localData[WGSH][WGSW];//w32h32c4\n" +" \n" +" #pragma unroll\n" +" for(int i=0; i= height || offset_w >= width) ? (INPUT_TYPE4)0 : vload4(0,input+(((b*channel_4+c4)*height+offset_h)*width+offset_w)*4);\n" +" }\n" +" }\n" +" \n" +" barrier(CLK_LOCAL_MEM_FENCE);\n" +" \n" +" // c4w32h32\n" +" int oh=ih*TSH >> 4;\n" +" int mh=ih & (16/TSH-1);\n" +" // TSW offset: [TSH/4,TSW/4,16/TSH]\n" +" int ow_base=jw*TSW;\n" +" int oh_offset=oh << 4;\n" +" //#pragma unroll\n" +" for(int i=0; i= width || h >= height || c >= channel);\n" +"#ifdef MNN_NHWC\n" +" #if defined(DIMENSION_3) && defined(TRANSPOSE)\n" +" // [N,W,H,1]\n" +" const int c_dst_pitch=1;\n" +" const int y_dst_pitch=c_dst_pitch*channelPad;\n" +" const int x_dst_pitch=y_dst_pitch*heightPad;\n" +" const int b_dst_pitch=x_dst_pitch*widthPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #elif defined(DIMENSION_4) && defined(TRANSPOSE)\n" +" // [N,H,C,W]\n" +" const int x_dst_pitch=1;\n" +" const int c_dst_pitch=x_dst_pitch*widthPad;\n" +" const int y_dst_pitch=c_dst_pitch*channelPad;\n" +" const int b_dst_pitch=y_dst_pitch*heightPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #elif defined(DIMENSION_3)\n" +" // [N,H,W,1]\n" +" const int c_dst_pitch=1;\n" +" const int x_dst_pitch=c_dst_pitch*channelPad;\n" +" const int y_dst_pitch=x_dst_pitch*widthPad;\n" +" const int b_dst_pitch=y_dst_pitch*heightPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #else\n" +" // [N,H,W,C]\n" +" const int c_dst_pitch=1;\n" +" const int x_dst_pitch=c_dst_pitch*channelPad;\n" +" const int y_dst_pitch=x_dst_pitch*widthPad;\n" +" const int b_dst_pitch=y_dst_pitch*heightPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #endif\n" +"#else\n" +" #if defined(DIMENSION_3) && defined(TRANSPOSE)\n" +" // [N,H,C,1]\n" +" const int x_dst_pitch=1;\n" +" const int c_dst_pitch=x_dst_pitch*widthPad;\n" +" const int y_dst_pitch=c_dst_pitch*channelPad;\n" +" const int b_dst_pitch=y_dst_pitch*heightPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" \n" +" #elif defined(DIMENSION_4) && defined(TRANSPOSE)\n" +" // [N,C,W,H]\n" +" const int y_dst_pitch=1;\n" +" const int x_dst_pitch=y_dst_pitch*heightPad;\n" +" const int c_dst_pitch=x_dst_pitch*widthPad;\n" +" const int b_dst_pitch=c_dst_pitch*channelPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #elif defined(DIMENSION_3)\n" +" // [N,C,H,1]\n" +" const int x_dst_pitch=1;\n" +" const int y_dst_pitch=x_dst_pitch*widthPad;\n" +" const int c_dst_pitch=y_dst_pitch*heightPad;\n" +" const int b_dst_pitch=c_dst_pitch*channelPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #else\n" +" // [N,C,H,W]\n" +" const int x_dst_pitch=1;\n" +" const int y_dst_pitch=x_dst_pitch*widthPad;\n" +" const int c_dst_pitch=y_dst_pitch*heightPad;\n" +" const int b_dst_pitch=c_dst_pitch*channelPad;\n" +" OUTPUT_TYPE4 value=outBound ? (OUTPUT_TYPE4)0 : CONVERT_OUTPUT4(vload4(0,input+b*b_src_pitch+c_4*c_src_pitch+h*y_src_pitch+w*x_src_pitch));\n" +" #endif\n" +"#endif\n" +" __global OUTPUT_TYPE* dst_ptr=output+b*b_dst_pitch+c*c_dst_pitch+h*y_dst_pitch+w*x_dst_pitch;\n" +" dst_ptr[0]=value.x;\n" +" if(c+1 >= channel)return;\n" +" dst_ptr[c_dst_pitch]=value.y;\n" +" if(c+2 >= channel)return;\n" +" dst_ptr[2*c_dst_pitch]=value.z;\n" +" if(c+3 >= channel)return;\n" +" dst_ptr[3*c_dst_pitch]=value.w;\n" +" }\n" +"}\n" +"__kernel void pack_buf(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __global INPUT_TYPE* input,__global OUTPUT_TYPE* output,\n" +" __private const int widthPad,\n" +" __private const int heightPad,\n" +" __private const int channelPad,\n" +" __private const int batch,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel){\n" +" int3 pos=(int3)(get_global_id(0),get_global_id(1),get_global_id(2));\n" +" if (pos.x= width || h >= height || c >= channel) {\n" +" return;\n" +" }\n" +" const int x_dst_pitch=4;\n" +" const int y_dst_pitch=x_dst_pitch*width;\n" +" const int c_dst_pitch=y_dst_pitch*height;\n" +" const int b_dst_pitch=c_dst_pitch*((channel+3)/4);\n" +"#ifdef MNN_NHWC\n" +" #if defined(TRANSPOSE) && defined(DIMENSION_3)\n" +" // [N,W,H,1]\n" +" const int c_src_pitch=1;\n" +" const int y_src_pitch=c_src_pitch;\n" +" const int x_src_pitch=y_src_pitch*heightPad;\n" +" const int b_src_pitch=x_src_pitch*widthPad;\n" +" #elif defined(TRANSPOSE) && defined(DIMENSION_4)\n" +" // [N,H,C,W]\n" +" const int x_src_pitch=1;\n" +" const int c_src_pitch=x_src_pitch*widthPad;\n" +" const int y_src_pitch=c_src_pitch*channelPad;\n" +" const int b_src_pitch=y_src_pitch*heightPad;\n" +" #else\n" +" // [N,H,W,C]\n" +" const int c_src_pitch=1;\n" +" const int x_src_pitch=c_src_pitch*channelPad;\n" +" const int y_src_pitch=x_src_pitch*widthPad;\n" +" const int b_src_pitch=y_src_pitch*heightPad;\n" +" #endif\n" +"#else\n" +" #if defined(TRANSPOSE) && defined(DIMENSION_3)\n" +" // dst:[N,C,H,1] -> src:[N,H,C,1]\n" +" const int x_src_pitch=1;\n" +" const int c_src_pitch=x_src_pitch*widthPad;\n" +" const int y_src_pitch=c_src_pitch*channelPad;\n" +" const int b_src_pitch=y_src_pitch*heightPad;\n" +" #elif defined(TRANSPOSE) && defined(DIMENSION_4)\n" +" // dst:[N,C,H,W] -> src:[N,C,W,H]\n" +" const int y_src_pitch=1;\n" +" const int x_src_pitch=y_src_pitch*heightPad;\n" +" const int c_src_pitch=x_src_pitch*widthPad;\n" +" const int b_src_pitch=c_src_pitch*channelPad;\n" +" #else\n" +" // [N,C,H,W]\n" +" const int x_src_pitch=1;\n" +" const int y_src_pitch=x_src_pitch*widthPad;\n" +" const int c_src_pitch=y_src_pitch*heightPad;\n" +" const int b_src_pitch=c_src_pitch*channelPad;\n" +" #endif\n" +"#endif\n" +" __global INPUT_TYPE* src_ptr=input+b*b_src_pitch+c*c_src_pitch+h*y_src_pitch+w*x_src_pitch;\n" +" OUTPUT_TYPE4 value=(OUTPUT_TYPE4)0;\n" +" OUTPUT_TYPE *value_ptr=(OUTPUT_TYPE*)&value;\n" +" for(int i=0; i<4 && (i+c= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define MIN_VALUE -FLT_MAX\n" +"// Supported data type: half/float\n" +"__kernel void roi_pooling(GLOBAL_SIZE_3_DIMS __read_only image2d_t input,__read_only image2d_t roi,\n" +" __private const int in_height,__private const int in_width,__private const int in_batch,\n" +" __private const int out_height,__private const int out_width,__private const float spatial_scale,\n" +" __write_only image2d_t output) {\n" +" const int out_channel_idx=get_global_id(0);\n" +" const int out_width_idx=get_global_id(1);\n" +" const int out_hb_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(out_channel_idx,out_width_idx,out_hb_idx);\n" +" const int roi_batch_idx=out_hb_idx/out_height;\n" +" const int out_height_idx=out_hb_idx % out_height;\n" +"#if defined ROI_C1H1W5\n" +" FLOAT4 roi_0=RI_F(roi,SAMPLER,(int2)(0,roi_batch_idx));\n" +" int input_batch=roi_0.x;\n" +" if(input_batch >= in_batch){\n" +" return;\n" +" }\n" +" FLOAT4 roi_1=RI_F(roi,SAMPLER,(int2)(1,roi_batch_idx));\n" +" FLOAT4 roi_2=RI_F(roi,SAMPLER,(int2)(2,roi_batch_idx));\n" +" FLOAT4 roi_3=RI_F(roi,SAMPLER,(int2)(3,roi_batch_idx));\n" +" FLOAT4 roi_4=RI_F(roi,SAMPLER,(int2)(4,roi_batch_idx));\n" +" int x1=round(roi_1.x*spatial_scale);\n" +" int y1=round(roi_2.x*spatial_scale);\n" +" int x2=round(roi_3.x*spatial_scale);\n" +" int y2=round(roi_4.x*spatial_scale);\n" +"#elif defined ROI_C5H1W1\n" +" FLOAT4 roi_0=RI_F(roi,SAMPLER,(int2)(0,roi_batch_idx));\n" +" int input_batch=roi_0.x;\n" +" if(input_batch >= in_batch){\n" +" return;\n" +" }\n" +" FLOAT4 roi_1=RI_F(roi,SAMPLER,(int2)(1,roi_batch_idx));\n" +" int x1=round(roi_0.y*spatial_scale);\n" +" int y1=round(roi_0.z*spatial_scale);\n" +" int x2=round(roi_0.w*spatial_scale);\n" +" int y2=round(roi_1.x*spatial_scale);\n" +"#else\n" +" const int roi_batch_offset=roi_batch_idx*5;\n" +" FLOAT4 roi_0=RI_F(roi,SAMPLER,(int2)(0,roi_batch_offset));\n" +" int input_batch=roi_0.x;\n" +" if(input_batch >= in_batch){\n" +" return;\n" +" }\n" +" FLOAT4 roi_1=RI_F(roi,SAMPLER,(int2)(0,roi_batch_offset+1));\n" +" FLOAT4 roi_2=RI_F(roi,SAMPLER,(int2)(0,roi_batch_offset+2));\n" +" FLOAT4 roi_3=RI_F(roi,SAMPLER,(int2)(0,roi_batch_offset+3));\n" +" FLOAT4 roi_4=RI_F(roi,SAMPLER,(int2)(0,roi_batch_offset+4));\n" +" int x1=round(roi_1.x*spatial_scale);\n" +" int y1=round(roi_2.x*spatial_scale);\n" +" int x2=round(roi_3.x*spatial_scale);\n" +" int y2=round(roi_4.x*spatial_scale);\n" +"#endif\n" +" int roiW=max(x2-x1+1,1);\n" +" int roiH=max(y2-y1+1,1);\n" +" float binSizeW=(float)roiW/(float)out_width;\n" +" float binSizeH=(float)roiH/(float)out_height;\n" +" int hStart=min(max(y1+(int)floor(out_height_idx*binSizeH),0),in_height);\n" +" int hEnd=min(max(y1+(int)ceil((out_height_idx+1)*binSizeH),0),in_height);\n" +" int hLen=hEnd-hStart;\n" +" int wStart=min(max(x1+(int)floor(out_width_idx*binSizeW),0),in_width);\n" +" int wEnd=min(max(x1+(int)ceil((out_width_idx+1)*binSizeW),0),in_width);\n" +" int wLen=wEnd-wStart;\n" +" const int pos=mad24(out_channel_idx,out_width,out_width_idx);\n" +" const FLOAT4 zero_vec=(FLOAT4)(0);\n" +" if (wLen <= 0 || hLen <= 0) {\n" +" WI_F(output,(int2)(pos,out_hb_idx),zero_vec);\n" +" return;\n" +" }\n" +" FLOAT4 res=(FLOAT4)(MIN_VALUE);\n" +" const int in_height_start=hStart;\n" +" const int in_width_start=wStart;\n" +" const int in_channel_offset=mul24(out_channel_idx,in_width);\n" +" const int in_height_offset=mul24(input_batch,in_height);\n" +" const int batch_idx=mul24(input_batch,in_height);\n" +" for (int height=0; height= inputShape.y)); "" inValue##i=RI_F(input,SAMPLER,(int2)(inOffset##i,inHeightIdx));\n" +"#define CALCULATE_OUTPUT(i) "" outValue##i = mad(inValue##i.x, weights0, outValue##i); "" outValue##i = mad(inValue##i.y, weights1, outValue##i); "" outValue##i = mad(inValue##i.z, weights2, outValue##i); "" outValue##i=mad(inValue##i.w,weights3,outValue##i);\n" +"#define GLOBAL_SIZE_2_DIMS __private const int global_size_dim0,__private const int global_size_dim1,\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"#define DEAL_NON_UNIFORM_DIM2(input1, input2) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1) { "" return; "" }\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void depthwise_conv2d_s1(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,__read_only image2d_t filter,\n" +" #ifndef NO_BIAS\n" +" __read_only image2d_t bias,\n" +" #endif\n" +" __write_only image2d_t output,\n" +" __private const int2 inputShape,\n" +" __private const int inChannelBlocks,\n" +" __private const int2 outputShape,\n" +" __private const int2 filterShape,\n" +" __private const int2 paddingShape) {\n" +" const int outChannelWidthIdx=get_global_id(0);\n" +" const int outHeightBlockIdx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(outChannelWidthIdx,outHeightBlockIdx);\n" +" int ow4=(outputShape.y+3)/4;\n" +" const int outChannelBlockIdx=outChannelWidthIdx/ow4;\n" +" const int outWidthBlockidx=outChannelWidthIdx % ow4;\n" +" const int inChannelBlockIdx=outChannelBlockIdx;\n" +" #ifndef NO_BIAS\n" +" FLOAT4 outValue0=RI_F(bias,SAMPLER,(int2)(outChannelBlockIdx,0));\n" +" #else\n" +" FLOAT4 outValue0=(FLOAT4)(0.0f);\n" +" #endif\n" +" FLOAT4 outValue1=outValue0;\n" +" FLOAT4 outValue2=outValue0;\n" +" FLOAT4 outValue3=outValue0;\n" +" const int outWidthBlockidx4=outWidthBlockidx << 2;\n" +" const int inWidthOffset0=outWidthBlockidx4-paddingShape.y;\n" +" const int inWidthOffset1=inWidthOffset0+1;\n" +" const int inWidthOffset2=inWidthOffset0+2;\n" +" const int inWidthOffset3=inWidthOffset0+3;\n" +" int heightIdx=outHeightBlockIdx % outputShape.x-paddingShape.x;\n" +" const int outBatchIdx=mul24((outHeightBlockIdx/outputShape.x),inputShape.x);\n" +" const int inCurIdx=mul24(inChannelBlockIdx,inputShape.y);\n" +" const int inWidthIdx0=select(inCurIdx+inWidthOffset0,-1,(inWidthOffset0<0 || inWidthOffset0 >= inputShape.y));\n" +" const int inWidthIdx1=select(inCurIdx+inWidthOffset1,-1,(inWidthOffset1<0 || inWidthOffset1 >= inputShape.y));\n" +" const int inWidthIdx2=select(inCurIdx+inWidthOffset2,-1,(inWidthOffset2<0 || inWidthOffset2 >= inputShape.y));\n" +" FLOAT4 inValue0,inValue1,inValue2,inValue3;\n" +" for (int kh=0; kh= inputShape.x));\n" +" heightIdx++;\n" +" inValue1=RI_F(input,SAMPLER,(int2)(inWidthIdx0,inHeightIdx));\n" +" inValue2=RI_F(input,SAMPLER,(int2)(inWidthIdx1,inHeightIdx));\n" +" inValue3=RI_F(input,SAMPLER,(int2)(inWidthIdx2,inHeightIdx));\n" +" for (int kw=0; kw= inputShape.y));\n" +" inValue3=RI_F(input,SAMPLER,(int2)(inWidthIdx,inHeightIdx));\n" +" FLOAT4 weights=RI_F(filter,SAMPLER,(int2)(filterIdx,inChannelBlockIdx));\n" +" outValue0=mad(inValue0,weights,outValue0);\n" +" outValue1=mad(inValue1,weights,outValue1);\n" +" outValue2=mad(inValue2,weights,outValue2);\n" +" outValue3=mad(inValue3,weights,outValue3);\n" +" }\n" +" }\n" +"#ifdef RELU\n" +" outValue0=fmax(outValue0,(FLOAT4)0);\n" +" outValue1=fmax(outValue1,(FLOAT4)0);\n" +" outValue2=fmax(outValue2,(FLOAT4)0);\n" +" outValue3=fmax(outValue3,(FLOAT4)0);\n" +"#endif\n" +"#ifdef RELU6\n" +" outValue0=clamp(outValue0,(FLOAT4)0,(FLOAT4)6);\n" +" outValue1=clamp(outValue1,(FLOAT4)0,(FLOAT4)6);\n" +" outValue2=clamp(outValue2,(FLOAT4)0,(FLOAT4)6);\n" +" outValue3=clamp(outValue3,(FLOAT4)0,(FLOAT4)6);\n" +"#endif\n" +" const int remain=outputShape.y-outWidthBlockidx4;\n" +" int outWidthIdx=mul24(outChannelBlockIdx,outputShape.y)+outWidthBlockidx4;\n" +" if (remain >= 4) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightBlockIdx),outValue0);\n" +" WI_F(output,(int2)(outWidthIdx+1,outHeightBlockIdx),outValue1);\n" +" WI_F(output,(int2)(outWidthIdx+2,outHeightBlockIdx),outValue2);\n" +" WI_F(output,(int2)(outWidthIdx+3,outHeightBlockIdx),outValue3);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightBlockIdx),outValue0);\n" +" WI_F(output,(int2)(outWidthIdx+1,outHeightBlockIdx),outValue1);\n" +" WI_F(output,(int2)(outWidthIdx+2,outHeightBlockIdx),outValue2);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightBlockIdx),outValue0);\n" +" WI_F(output,(int2)(outWidthIdx+1,outHeightBlockIdx),outValue1);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightBlockIdx),outValue0);\n" +" }\n" +"}\n" +"__kernel\n" +"#if SET_ATTRIBUTE\n" +"__attribute__((work_group_size_hint(16,16,1)))\n" +"#endif\n" +"void depthwise_conv2d(GLOBAL_SIZE_2_DIMS __read_only image2d_t input,__read_only image2d_t filter,\n" +" #ifndef NO_BIAS\n" +" __read_only image2d_t bias,\n" +" #endif\n" +" __write_only image2d_t output,\n" +" __private const int2 inputShape,\n" +" __private const int inChannelBlocks,__private const int2 outputShape,\n" +" __private const int2 filterShape,\n" +" __private const int2 paddingShape,\n" +" __private const int2 dilationShape,\n" +" __private const int2 strideShape) {\n" +" const int outChannelWidthIdx=get_global_id(0);\n" +" const int outHeightIdx=get_global_id(1);\n" +" DEAL_NON_UNIFORM_DIM2(outChannelWidthIdx,outHeightIdx);\n" +" int ow4=(outputShape.y+3)/4;\n" +" const int outChannelBlockIdx=outChannelWidthIdx/ow4;\n" +" const int outWidthBlockidx=outChannelWidthIdx % ow4;\n" +" const int inChannelBlockIdx=outChannelBlockIdx;\n" +" #ifndef NO_BIAS\n" +" FLOAT4 outValue0=RI_F(bias,SAMPLER,(int2)(outChannelBlockIdx,0));\n" +" #else\n" +" FLOAT4 outValue0=(FLOAT4)(0.0f);\n" +" #endif\n" +" FLOAT4 outValue1=outValue0;\n" +" FLOAT4 outValue2=outValue0;\n" +" FLOAT4 outValue3=outValue0;\n" +" const int inWidthOffset0=mad24(outWidthBlockidx,strideShape.y << 2,-paddingShape.y);\n" +" const int inWidthOffset1=inWidthOffset0+strideShape.y;\n" +" const int inWidthOffset2=inWidthOffset1+strideShape.y;\n" +" const int inWidthOffset3=inWidthOffset2+strideShape.y;\n" +" int heightIdx=mad24(outHeightIdx % outputShape.x,strideShape.x,-paddingShape.x);\n" +" const int outBatchIdx=mul24((outHeightIdx/outputShape.x),inputShape.x);\n" +" const int inCurIdx=mul24(inChannelBlockIdx,inputShape.y);\n" +" for (int kh=0; kh= inputShape.x));\n" +" heightIdx += dilationShape.x;\n" +" for (int kw=0; kw= 4) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightIdx),outValue0);\n" +" WI_F(output,(int2)(outWidthIdx+1,outHeightIdx),outValue1);\n" +" WI_F(output,(int2)(outWidthIdx+2,outHeightIdx),outValue2);\n" +" WI_F(output,(int2)(outWidthIdx+3,outHeightIdx),outValue3);\n" +" } else if (remain == 3) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightIdx),outValue0);\n" +" WI_F(output,(int2)(outWidthIdx+1,outHeightIdx),outValue1);\n" +" WI_F(output,(int2)(outWidthIdx+2,outHeightIdx),outValue2);\n" +" } else if (remain == 2) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightIdx),outValue0);\n" +" WI_F(output,(int2)(outWidthIdx+1,outHeightIdx),outValue1);\n" +" } else if (remain == 1) {\n" +" WI_F(output,(int2)(outWidthIdx,outHeightIdx),outValue0);\n" +" }\n" +"}\n" +; +const char* layernorm = +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void layernorm_w(__private int global_dim0,__private int global_dim1,__private int global_dim2,\n" +" __read_only image2d_t input,\n" +" __write_only image2d_t output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channel,\n" +"#ifdef GAMMA_BETA\n" +" __global const FLOAT *gamma,\n" +" __global const FLOAT *beta,\n" +"#endif\n" +" __private float epsilon){\n" +" int3 pos=(int3)(get_global_id(0),get_global_id(1),get_global_id(2));\n" +" float4 local sum[LOCAL_SIZE];\n" +" if (pos.x0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid0; i /= 2){\n" +" if (lid= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__kernel void cast_buf(GLOBAL_SIZE_3_DIMS\n" +" __global INPUT_TYPE* input,\n" +" __global OUTPUT_TYPE* output,\n" +" __private const int width,\n" +" __private const int height,\n" +" __private const int channelBlock\n" +" ) {\n" +" const int width_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/channelBlock;\n" +" const int channel_idx=batch_channel_idx % channelBlock;\n" +" \n" +" const int inp_offset=((((batch_idx*channelBlock)+channel_idx)*height+height_idx)*width+width_idx)*4;\n" +"#ifdef TO_BOOL\n" +" int4 value=convert_int4(vload4(0,input+inp_offset));\n" +" value=value == (int4)0 ? (int4)0 : (int4)1;\n" +" vstore4(CONVERT_OUTPUT4(value),0,output+inp_offset);\n" +"#else\n" +" vstore4(CONVERT_OUTPUT4(vload4(0,input+inp_offset)),0,output+inp_offset);\n" +"#endif\n" +"}\n" +; +#endif +const char* reduction = +"// TODO: use INIT_SCALAR_VALUE,OPERATOR,FINAL_OPERATOR_ON_CHANNEL macro abstract and simplify code\n" +"// TODO: support reduce dims include batch\n" +"// TODO: support keep_dim=False\n" +"// TODO: fix channel reduce result re-pack problem\n" +"#ifdef MNN_SUPPORT_FP16\n" +"#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n" +"#endif\n" +"#define GLOBAL_SIZE_3_DIMS "" __private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define GLOBAL_SIZE_2_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,\n" +"#define GLOBAL_SIZE_3_DIMS ""__private const int global_size_dim0,__private const int global_size_dim1,__private const int global_size_dim2,\n" +"#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) "" if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { "" return; "" }\n" +"__constant sampler_t SAMPLER=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;\n" +"__kernel void reduct_width(GLOBAL_SIZE_3_DIMS\n" +" __read_only image2d_t input,\n" +" __write_only image2d_t output,\n" +" __private const int inputWidth,\n" +" __private const int inputHeight,\n" +" __private const int inputChannel,\n" +" __private const int inputBatch,\n" +" __private const int inputChannelBlock,\n" +" __private const int oututWidth,\n" +" __private const int outputHeight,\n" +" __private const int outputChannel,\n" +" __private const int outputChannelBlock\n" +" ) {\n" +" const int width_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int batch_idx=batch_channel_idx/outputChannelBlock;\n" +" const int channel_idx=batch_channel_idx % outputChannelBlock;\n" +" const int bh=batch_idx*inputHeight+height_idx;\n" +" const int wc=channel_idx*inputWidth;\n" +" INPUT_TYPE_I4 out=(INPUT_TYPE_I4)VALUE;\n" +" \n" +"#if LOCAL_SIZE>0\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE_I4 local sum[LOCAL_SIZE];\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,batch_channel_idx);\n" +" \n" +" const int width_idx=get_group_id(0);\n" +" const int batch_idx=batch_channel_idx/outputChannelBlock;\n" +" const int channel_idx=batch_channel_idx % outputChannelBlock;\n" +" \n" +" const int bh=batch_idx*inputHeight;\n" +" const int wc=channel_idx*inputWidth+width_idx;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE_I4 local sum[LOCAL_SIZE];\n" +" INPUT_TYPE_I4 out=(INPUT_TYPE_I4)VALUE;\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int batch_idx=get_global_id(2);\n" +" \n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,batch_idx);\n" +" const int width_idx=get_group_id(0);\n" +" \n" +" const int bh=batch_idx*inputHeight+height_idx;\n" +" const int wc=width_idx;\n" +" int remain=inputChannel-(inputChannelBlock-1)*4;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE_I local sum[LOCAL_SIZE];\n" +" INPUT_TYPE_I4 out=(INPUT_TYPE_I4)VALUE;\n" +" INPUT_TYPE_I4 in;\n" +" INPUT_TYPE_I *inPtr=(INPUT_TYPE_I*)∈\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid0\n" +" const int width_local_idx=get_global_id(0);\n" +" const int height_idx=get_global_id(1);\n" +" const int channel_idx=get_global_id(2);\n" +" DEAL_NON_UNIFORM_DIM3(width_local_idx,height_idx,channel_idx);\n" +" const int width_idx=get_group_id(0);\n" +" \n" +" const int bh=height_idx;\n" +" const int wc=channel_idx*inputWidth+width_idx;\n" +" int batchOffset=inputChannelBlock*inputHeight*inputWidth;\n" +" const int lid=get_local_id(0);\n" +" INPUT_TYPE_I4 local sum[LOCAL_SIZE];\n" +" INPUT_TYPE_I4 out=(INPUT_TYPE_I4)VALUE;\n" +" for(int i=lid; i0; i /= 2){\n" +" if (lid +#include +#include +#include +namespace MNN { +extern const char* conv_2d; +extern const char* deconv_2d; +extern const char* unary; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* grid_sample_buf; +#endif +extern const char* interp; +extern const char* select; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* range_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* self_attention_buf; +#endif +extern const char* performance; +extern const char* winogradTransformSource2_3_1; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* gemv_conv1x1_buf; +#endif +extern const char* raster; +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* conv_2d_c1_subgroup_buf; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* matmul_local_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* conv_2d_int_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* interp_buf; +#endif +extern const char* scale; +extern const char* softmax; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* binary_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* gemm_quant_batch_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* raster_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* binary_subgroup_buf; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* depthwise_conv2d_subgroup_buf; +#endif +#endif +extern const char* nearest; +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* pooling_subgroup_buf; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* pooling_buf; +#endif +extern const char* winogradTransformSource2_5_1; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* unary_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* depthwise_conv2d_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* winogradTransform_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* winogradTransform_subgroup_buf; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* splitgelu_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* select_buf; +#endif +extern const char* grid_sample; +extern const char* buffer_convert_quant; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* gemm_buf; +#endif +extern const char* copy_buffer_to_image2d; +extern const char* loop; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* argmax_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* buffer_convert_subgroup_buf; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* attention_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* groupnorm_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* unary_subgroup_buf; +#endif +#endif +extern const char* gemm; +extern const char* depthwise_deconv2d; +extern const char* range; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* scale_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* matmul_buf; +#endif +extern const char* pooling; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* conv_2d_buf; +#endif +extern const char* buffer_to_image; +extern const char* winogradTransformDest2_3_1; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* layernorm_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* softmax_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* gather_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP +extern const char* conv_2d_c16_subgroup_buf; +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* input_transe_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* reduction_buf; +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* matmul_params_buf; +#endif +extern const char* cast; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* buffer_convert_buf; +#endif +extern const char* matmul; +extern const char* binary; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* loop_buf; +#endif +extern const char* roi_pooling; +extern const char* depthwise_conv2d; +extern const char* layernorm; +extern const char* winogradTransformDest2_5_1; +#ifndef MNN_OPENCL_BUFFER_CLOSED +extern const char* cast_buf; +#endif +extern const char* reduction; +const std::map OpenCLProgramMap = + { + { "conv_2d", conv_2d }, + { "deconv_2d", deconv_2d }, + { "unary", unary }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "grid_sample_buf", grid_sample_buf }, +#endif + { "interp", interp }, + { "select", select }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "range_buf", range_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "self_attention_buf", self_attention_buf }, +#endif + { "performance", performance }, + { "winogradTransformSource2_3_1", winogradTransformSource2_3_1 }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "gemv_conv1x1_buf", gemv_conv1x1_buf }, +#endif + { "raster", raster }, +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "conv_2d_c1_subgroup_buf", conv_2d_c1_subgroup_buf }, +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "matmul_local_buf", matmul_local_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "conv_2d_int_buf", conv_2d_int_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "interp_buf", interp_buf }, +#endif + { "scale", scale }, + { "softmax", softmax }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "binary_buf", binary_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "gemm_quant_batch_buf", gemm_quant_batch_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "raster_buf", raster_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "binary_subgroup_buf", binary_subgroup_buf }, +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "depthwise_conv2d_subgroup_buf", depthwise_conv2d_subgroup_buf }, +#endif +#endif + { "nearest", nearest }, +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "pooling_subgroup_buf", pooling_subgroup_buf }, +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "pooling_buf", pooling_buf }, +#endif + { "winogradTransformSource2_5_1", winogradTransformSource2_5_1 }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "unary_buf", unary_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "depthwise_conv2d_buf", depthwise_conv2d_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "winogradTransform_buf", winogradTransform_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "winogradTransform_subgroup_buf", winogradTransform_subgroup_buf }, +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "splitgelu_buf", splitgelu_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "select_buf", select_buf }, +#endif + { "grid_sample", grid_sample }, + { "buffer_convert_quant", buffer_convert_quant }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "gemm_buf", gemm_buf }, +#endif + { "copy_buffer_to_image2d", copy_buffer_to_image2d }, + { "loop", loop }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "argmax_buf", argmax_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "buffer_convert_subgroup_buf", buffer_convert_subgroup_buf }, +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "attention_buf", attention_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "groupnorm_buf", groupnorm_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "unary_subgroup_buf", unary_subgroup_buf }, +#endif +#endif + { "gemm", gemm }, + { "depthwise_deconv2d", depthwise_deconv2d }, + { "range", range }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "scale_buf", scale_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "matmul_buf", matmul_buf }, +#endif + { "pooling", pooling }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "conv_2d_buf", conv_2d_buf }, +#endif + { "buffer_to_image", buffer_to_image }, + { "winogradTransformDest2_3_1", winogradTransformDest2_3_1 }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "layernorm_buf", layernorm_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "softmax_buf", softmax_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "gather_buf", gather_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED +#ifdef MNN_SUPPORT_INTEL_SUBGROUP + { "conv_2d_c16_subgroup_buf", conv_2d_c16_subgroup_buf }, +#endif +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "input_transe_buf", input_transe_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "reduction_buf", reduction_buf }, +#endif +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "matmul_params_buf", matmul_params_buf }, +#endif + { "cast", cast }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "buffer_convert_buf", buffer_convert_buf }, +#endif + { "matmul", matmul }, + { "binary", binary }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "loop_buf", loop_buf }, +#endif + { "roi_pooling", roi_pooling }, + { "depthwise_conv2d", depthwise_conv2d }, + { "layernorm", layernorm }, + { "winogradTransformDest2_5_1", winogradTransformDest2_5_1 }, +#ifndef MNN_OPENCL_BUFFER_CLOSED + { "cast_buf", cast_buf }, +#endif + { "reduction", reduction }, +}; +} diff --git a/source/backend/opencl/execution/cl/self_attention_buf.cl b/source/backend/opencl/execution/cl/self_attention_buf.cl new file mode 100644 index 000000000..00529ef8d --- /dev/null +++ b/source/backend/opencl/execution/cl/self_attention_buf.cl @@ -0,0 +1,364 @@ +#ifdef MNN_SUPPORT_FP16 +#pragma OPENCL EXTENSION cl_khr_fp16 : enable +#endif + +#define GLOBAL_SIZE_3_DIMS \ + __private const int global_size_dim0, __private const int global_size_dim1, __private const int global_size_dim2, + +#define DEAL_NON_UNIFORM_DIM3(input1, input2, input3) \ + if (input1 >= global_size_dim0 || input2 >= global_size_dim1 || input3 >= global_size_dim2) { \ + return; \ + } + +#define DEAL_HEAD_DIM_NOT_ALIGN \ + if(hd * 4 + 3 >= head_dim) {\ + temp_0.w = (FLOAT)0;\ + temp_1.w = (FLOAT)0;\ + temp_2.w = (FLOAT)0;\ + temp_3.w = (FLOAT)0;\ + }\ + if(hd * 4 + 2 >= head_dim) {\ + temp_0.z = (FLOAT)0;\ + temp_1.z = (FLOAT)0;\ + temp_2.z = (FLOAT)0;\ + temp_3.z = (FLOAT)0;\ + }\ + if(hd * 4 + 1 >= head_dim) {\ + temp_0.y = (FLOAT)0;\ + temp_1.y = (FLOAT)0;\ + temp_2.y = (FLOAT)0;\ + temp_3.y = (FLOAT)0;\ + } + +#define DEAL_SEQ_LEN_NOT_ALIGN \ + if(4 * sl + 3 >= seq_len) {\ + temp_3 = (FLOAT4)0;\ + }\ + if(4 * sl + 2 >= seq_len) {\ + temp_2 = (FLOAT4)0;\ + }\ + if(4 * sl + 1 >= seq_len) {\ + temp_1 = (FLOAT4)0;\ + } + +__kernel void split_transpose_qkv(GLOBAL_SIZE_3_DIMS + __global const FLOAT *input, // [Batch, seqLen/4, mNumHead * 3 * mHeadDim, 4] + __global FLOAT *output_q, // [Batch * mNumHead, head_dim_pack_k, seq_len_pack_mn / qSeqSplitNum] + __global FLOAT *output_k, // [Batch * mNumHead, head_dim_pack_k, seq_len_pack_mn] + __global FLOAT *output_v, // [Batch * mNumHead, ROUND_UP(seqLen, tile), head_dim_pack_mn] + __private const int seq_len_pack_mn, + __private const int seq_len_piece, + __private const int head_dim_pack_mn, + __private const int head_dim_pack_k, + __private const int seq_len, + __private const int head_num, + __private const int head_dim, + __private const int seq_index +) { + const int sl = get_global_id(0); // seqLen_4 + const int hd = get_global_id(1); // mHeadDim_4 + const int z = get_global_id(2); // Batch * mNumHead + DEAL_NON_UNIFORM_DIM3(sl, hd, z); + + const int b = z / head_num; + const int hn = z % head_num; + + const int seq_len_4 = (seq_len + 3) / 4; + const int offset_q = ((b * head_num + hn) * head_dim_pack_k + 4 * hd) * seq_len_piece + 4 * sl; + + if(seq_index > 0) { + // fill output_q only + if(sl * 4 >= seq_len || hd * 4 >= head_dim) { + if(hd * 4 < head_dim_pack_k) { + if(sl * 4 < seq_len_piece) { + vstore4((FLOAT4)0, 0, output_q + offset_q); + vstore4((FLOAT4)0, 0, output_q + offset_q + seq_len_piece); + vstore4((FLOAT4)0, 0, output_q + offset_q + seq_len_piece + seq_len_piece); + vstore4((FLOAT4)0, 0, output_q + offset_q + seq_len_piece + seq_len_piece + seq_len_piece); + } + } + return; + } + + const int offset_inp = (((b * seq_len_4 + seq_index * seq_len_piece / 4 + sl) * head_num + hn) * 3 * head_dim + 4 * hd) * 4; + + if(sl * 4 < seq_len_piece) { + FLOAT4 temp_0 = vload4(0, input + offset_inp); + FLOAT4 temp_1 = vload4(0, input + offset_inp + 4); + FLOAT4 temp_2 = vload4(0, input + offset_inp + 8); + FLOAT4 temp_3 = vload4(0, input + offset_inp + 12); + #ifdef HEADDIM_LEAVE + DEAL_HEAD_DIM_NOT_ALIGN + #endif + #ifdef SEQLEN_LEAVE + DEAL_SEQ_LEN_NOT_ALIGN + #endif + vstore4(temp_0, 0, output_q + offset_q); + vstore4(temp_1, 0, output_q + offset_q + seq_len_piece); + vstore4(temp_2, 0, output_q + offset_q + seq_len_piece + seq_len_piece); + vstore4(temp_3, 0, output_q + offset_q + seq_len_piece + seq_len_piece + seq_len_piece); + } + return; + } + const int offset_k = ((b * head_num + hn) * head_dim_pack_k + 4 * hd) * seq_len_pack_mn + 4 * sl; + + const int offset_v = ((b * head_num + hn) * seq_len_pack_mn + 4 * sl) * head_dim_pack_mn + 4 * hd; + if(sl * 4 >= seq_len || hd * 4 >= head_dim) { + if(hd * 4 < head_dim_pack_k) { + if(sl * 4 < seq_len_piece) { + vstore4((FLOAT4)0, 0, output_q + offset_q); + vstore4((FLOAT4)0, 0, output_q + offset_q + seq_len_piece); + vstore4((FLOAT4)0, 0, output_q + offset_q + seq_len_piece + seq_len_piece); + vstore4((FLOAT4)0, 0, output_q + offset_q + seq_len_piece + seq_len_piece + seq_len_piece); + } + vstore4((FLOAT4)0, 0, output_k + offset_k); + vstore4((FLOAT4)0, 0, output_k + offset_k + seq_len_pack_mn); + vstore4((FLOAT4)0, 0, output_k + offset_k + seq_len_pack_mn + seq_len_pack_mn); + vstore4((FLOAT4)0, 0, output_k + offset_k + seq_len_pack_mn + seq_len_pack_mn + seq_len_pack_mn); + } + vstore4((FLOAT4)0, 0, output_v + offset_v); + vstore4((FLOAT4)0, 0, output_v + offset_v + head_dim_pack_mn); + vstore4((FLOAT4)0, 0, output_v + offset_v + head_dim_pack_mn + head_dim_pack_mn); + vstore4((FLOAT4)0, 0, output_v + offset_v + head_dim_pack_mn + head_dim_pack_mn + head_dim_pack_mn); + + return; + } + + + const int offset_inp = (((b * seq_len_4 + sl) * head_num + hn) * 3 * head_dim + 4 * hd) * 4; + + if(sl * 4 < seq_len_piece) { + FLOAT4 temp_0 = vload4(0, input + offset_inp); + FLOAT4 temp_1 = vload4(0, input + offset_inp + 4); + FLOAT4 temp_2 = vload4(0, input + offset_inp + 8); + FLOAT4 temp_3 = vload4(0, input + offset_inp + 12); + #ifdef HEADDIM_LEAVE + DEAL_HEAD_DIM_NOT_ALIGN + #endif + #ifdef SEQLEN_LEAVE + DEAL_SEQ_LEN_NOT_ALIGN + #endif + vstore4(temp_0, 0, output_q + offset_q); + vstore4(temp_1, 0, output_q + offset_q + seq_len_piece); + vstore4(temp_2, 0, output_q + offset_q + seq_len_piece + seq_len_piece); + vstore4(temp_3, 0, output_q + offset_q + seq_len_piece + seq_len_piece + seq_len_piece); + } + + { + // K + FLOAT4 temp_0 = vload4(0, input + offset_inp + 4*head_dim); + FLOAT4 temp_1 = vload4(0, input + offset_inp + 4*head_dim + 4); + FLOAT4 temp_2 = vload4(0, input + offset_inp + 4*head_dim + 8); + FLOAT4 temp_3 = vload4(0, input + offset_inp + 4*head_dim + 12); + #ifdef HEADDIM_LEAVE + DEAL_HEAD_DIM_NOT_ALIGN + #endif + #ifdef SEQLEN_LEAVE + DEAL_SEQ_LEN_NOT_ALIGN + #endif + + vstore4(temp_0, 0, output_k + offset_k); + vstore4(temp_1, 0, output_k + offset_k + seq_len_pack_mn); + vstore4(temp_2, 0, output_k + offset_k + seq_len_pack_mn + seq_len_pack_mn); + vstore4(temp_3, 0, output_k + offset_k + seq_len_pack_mn + seq_len_pack_mn + seq_len_pack_mn); + + // V + temp_0 = vload4(0, input + offset_inp + 8 * head_dim); + temp_1 = vload4(0, input + offset_inp + 8 * head_dim + 4); + temp_2 = vload4(0, input + offset_inp + 8 * head_dim + 8); + temp_3 = vload4(0, input + offset_inp + 8 * head_dim + 12); + #ifdef HEADDIM_LEAVE + DEAL_HEAD_DIM_NOT_ALIGN + #endif + #ifdef SEQLEN_LEAVE + DEAL_SEQ_LEN_NOT_ALIGN + #endif + + vstore4((FLOAT4){temp_0.x, temp_1.x, temp_2.x, temp_3.x}, 0, output_v + offset_v); + vstore4((FLOAT4){temp_0.y, temp_1.y, temp_2.y, temp_3.y}, 0, output_v + offset_v + head_dim_pack_mn); + vstore4((FLOAT4){temp_0.z, temp_1.z, temp_2.z, temp_3.z}, 0, output_v + offset_v + head_dim_pack_mn + head_dim_pack_mn); + vstore4((FLOAT4){temp_0.w, temp_1.w, temp_2.w, temp_3.w}, 0, output_v + offset_v + head_dim_pack_mn + head_dim_pack_mn + head_dim_pack_mn); + } +} + + +#ifndef SOFTMAX_LOCAL_SIZE + #define SOFTMAX_LOCAL_SIZE 512 +#endif + +// [outside, axis, inside] -> reduce: inside +__kernel void softmax_inside(GLOBAL_SIZE_3_DIMS + __global const FLOAT *input, // [batch * mNumHead, ROUND_UP(seqLen, tile), ROUND_UP(seqLen, tile)] + __global FLOAT *output, + __private const int inside_len, + __private const int4 shape // [batch * mNumHead, ROUND_UP(seqLen, tile), ROUND_UP(seqLen, tile)] + ) { + const int inside = get_global_id(0); + const int axis = get_global_id(1); + const int outside = get_global_id(2); + DEAL_NON_UNIFORM_DIM3(inside, axis, outside); + + const int offset = (outside * shape.y + axis) * shape.z + 0; + + int lid = get_local_id(0); + float local sum[SOFTMAX_LOCAL_SIZE]; + + /*Compute Max */ + float maxValue = (float)(-FLT_MAX); + // clip to seq_len + for (int i=lid; i 0; i /= 2){ + if (lid < i) + sum[lid] = fmax(sum[lid], sum[lid + i]); + barrier(CLK_LOCAL_MEM_FENCE); + } + maxValue = sum[0]; + + /*Compute Exp Sum*/ + float sumValue = 0; + for (int i=lid; i 0; i /= 2){ + if (lid < i) + sum[lid] = sum[lid] + sum[lid + i]; + barrier(CLK_LOCAL_MEM_FENCE); + } + sumValue = sum[0]; + + #ifdef OUTPUT_TRANSPOSE + const int out_offset = (outside * shape.z + 0) * shape.y + axis; + #endif + /*Compute Result */ + for (int i=lid; i [N Y X] +__kernel void trans_3d_buf(__global const FLOAT* input, + __global FLOAT* output, + __private const int batch, + __private const int width, + __private const int height +) { + int b = get_global_id(2); + + const int lidw = get_local_id(0); + const int lidh = get_local_id(1); + // group id + const int w = get_group_id(0) * WGSW; + const int h = get_group_id(1) * WGSH; + + int iw = lidw; + int jh = lidh; + + __local FLOAT4 localData[WGSW][WGSH/4];//w64h64 + + #pragma unroll + for(int i = 0; i < TSW; i++) { + int offset_w = i * WGSW / TSW + iw; + #pragma unroll + for(int j = 0; j < TSH / 4; j++) { + int offset_h = j * WGSH / TSH + jh; + // [TSW, WGSW / TSW] [TSH / 4, WGSH / TSH, 4] + localData[offset_w][offset_h] = vload4(0, input + ((b * width + (w+offset_w)) * height/4 + (h/4+offset_h)) * 4); + } + } + + barrier(CLK_LOCAL_MEM_FENCE); + + // H offset: [WGSH / TSH, TSH / 4, 4] + // W offset: [WGSW / TSW, TSW / 4, 4] + int oh_base = jh * TSH / 4; + int ow_base = iw * TSW / 4; + + //#pragma unroll + for(int j = 0; j < TSH / 4; j++) { + int oh = oh_base + j; + + //#pragma unroll + for(int i = 0; i < TSW / 4; i++) { + int ow = ow_base + i; + + FLOAT4 value_0 = (localData[4*ow][oh]); + FLOAT4 value_1 = (localData[4*ow+1][oh]); + FLOAT4 value_2 = (localData[4*ow+2][oh]); + FLOAT4 value_3 = (localData[4*ow+3][oh]); + vstore4((FLOAT4){value_0.x, value_1.x, value_2.x, value_3.x}, 0, output + ((b * height + h + 4*oh+0) * width + w + 4 * ow)); + vstore4((FLOAT4){value_0.y, value_1.y, value_2.y, value_3.y}, 0, output + ((b * height + h + 4*oh+1) * width + w + 4 * ow)); + vstore4((FLOAT4){value_0.z, value_1.z, value_2.z, value_3.z}, 0, output + ((b * height + h + 4*oh+2) * width + w + 4 * ow)); + vstore4((FLOAT4){value_0.w, value_1.w, value_2.w, value_3.w}, 0, output + ((b * height + h + 4*oh+3) * width + w + 4 * ow)); + } + } +} + + +__kernel void clip_transpose_qkv(GLOBAL_SIZE_3_DIMS + __global const FLOAT *input, // [Batch * mNumHead, ROUND_UP(mHeadDim, tile), ROUND_UP(seqLen, tile)] + __global FLOAT *output, // [Batch, seqLen/4, mNumHead * mHeadDim, 4] + __private const int tile, + __private const int seq_len, + __private const int seq_len_piece, + __private const int head_num, + __private const int head_dim, + __private const int seq_index +) { + + const int sl = get_global_id(0); // seqLen_Piece_4 + const int hd = get_global_id(1); // mHeadDim_4 + const int z = get_global_id(2); // Batch * mNumHead + DEAL_NON_UNIFORM_DIM3(sl, hd, z); + + const int b = z / head_num; + const int hn = z % head_num; + + const int seq_len_4 = (seq_len + 3) / 4; + + if(seq_index * seq_len_piece / 4 + sl >= seq_len_4) { + return; + } + const int seq_len_pack = seq_len_piece;//((seq_len + tile - 1) / tile) * tile; + const int head_dim_pack = ((head_dim + tile - 1) / tile) * tile; + + const int offset_inp = ((b * head_num + hn) * head_dim_pack + 4 * hd) * seq_len_pack + 4 * sl; + + const int offset_out = (((b * seq_len_4 + seq_index * seq_len_piece / 4 + sl) * head_num + hn) * head_dim + 4 * hd) * 4; + + // Q + FLOAT4 temp_0 = vload4(0, input + offset_inp); + FLOAT4 temp_1 = vload4(0, input + offset_inp + seq_len_pack); + FLOAT4 temp_2 = vload4(0, input + offset_inp + 2 * seq_len_pack); + FLOAT4 temp_3 = vload4(0, input + offset_inp + 3 * seq_len_pack); + + vstore4(temp_0, 0, output + offset_out); + if(4 * hd + 1 > head_dim) return; + vstore4(temp_1, 0, output + offset_out + 4); + if(4 * hd + 2 > head_dim) return; + vstore4(temp_2, 0, output + offset_out + 8); + if(4 * hd + 3 > head_dim) return; + vstore4(temp_3, 0, output + offset_out + 12); + +} diff --git a/source/backend/opencl/execution/cl/splitgelu_buf.cl b/source/backend/opencl/execution/cl/splitgelu_buf.cl new file mode 100644 index 000000000..e65e35736 --- /dev/null +++ b/source/backend/opencl/execution/cl/splitgelu_buf.cl @@ -0,0 +1,60 @@ +#ifdef MNN_SUPPORT_FP16 +#pragma OPENCL EXTENSION cl_khr_fp16 : enable +#endif + +__kernel void splitgelu_buf(__private int global_dim0, __private int global_dim1, __private int global_dim2, + __global const FLOAT * input, + #ifdef DOUBLE_INPUTS + __global const FLOAT * input1, + #endif + __global FLOAT * output, + __private const int4 shape +){ + int3 pos = (int3)(get_global_id(0), get_global_id(1), get_global_id(2)); + if (pos.x < global_dim0 && pos.y < global_dim1 && pos.z < global_dim2) { + const int b = pos.x; + const int c_4 = pos.y; + +// The product of W and H is a multiple of 4 +#ifdef WH_4 + const int hw_4 = pos.z; + + const int channel_4 = (shape.y + 3) >> 2; + const int area_4 = (shape.z + 3) >> 2; + const int in_offset = ((b * channel_4 + c_4) * area_4 * 2 + hw_4) * 16; + const int out_offset = ((b * channel_4 + c_4) * area_4 + hw_4) * 16; + + float16 valueL = convert_float16(vload16(0, input + in_offset)); + float16 valueR = convert_float16(vload16(area_4, input + in_offset)); + + #ifdef DOUBLE_INPUTS + float4 valueConstL = convert_float4(vload4(hw, input1)); + float4 valueConstR = convert_float4(vload4(area_4+hw, input1)); + valueL += (float16)((float4)valueConstL.x, (float4)valueConstL.y, (float4)valueConstL.z, (float4)valueConstL.w); + valueR += (float16)((float4)valueConstR.x, (float4)valueConstR.y, (float4)valueConstR.z, (float4)valueConstR.w); + #endif + float16 out = (erf(valueR * (float16)0.7071067932881648) + (float16)1.0) * valueR * (float16)0.5; + out *= valueL; + vstore16(CONVERT_FLOAT16(out), 0, output + out_offset); +#else + const int hw = pos.z; + + const int channel_4 = (shape.y + 3) >> 2; + const int in_offset = ((b * channel_4 + c_4) * shape.z * 2 + hw) * 4; + const int out_offset = ((b * channel_4 + c_4) * shape.z + hw) * 4; + + float4 valueL = convert_float4(vload4(0, input + in_offset)); + float4 valueR = convert_float4(vload4(shape.z, input + in_offset)); + + #ifdef DOUBLE_INPUTS + float valueConstL = input1[hw]; + float valueConstR = input1[shape.z+hw]; + valueL += (float4)valueConstL; + valueR += (float4)valueConstR; + #endif + float4 out = (erf(valueR * (float4)0.7071067932881648) + (float4)1.0) * valueR * (float4)0.5; + out *= valueL; + vstore4(CONVERT_FLOAT4(out), 0, output + out_offset); +#endif + } +} diff --git a/source/backend/opencl/execution/cl/winogradTransform_buf.cl b/source/backend/opencl/execution/cl/winogradTransform_buf.cl index 6803850e7..efb799643 100644 --- a/source/backend/opencl/execution/cl/winogradTransform_buf.cl +++ b/source/backend/opencl/execution/cl/winogradTransform_buf.cl @@ -10,6 +10,85 @@ return; \ } +// [dstChannel, srcChannel, 3, 3] -> [4x4, srcChannelPad, dstChannelpad] (N, Kpad, Npad) +__kernel void winoTransWeightBuf2_3_1(GLOBAL_SIZE_DIM2 + __global const float* input, // 0 + __global FLOAT* output, + __private const int srcChannel, // 3 + __private const int dstChannel, + __private const int srcChannelPad, // 6 + __private const int dstChannelPad +) { + int2 pos = (int2)(get_global_id(0), get_global_id(1)); + UNIFORM_BOUNDRY_CHECK(pos.x, pos.y); + + const int src_c = pos.x; + const int dst_c = pos.y; + + const int out_offset = (0 * srcChannelPad + src_c) * dstChannelPad + dst_c; + const int out_offset_add = srcChannelPad * dstChannelPad; + if(src_c >= srcChannel || dst_c >= dstChannel) { + for(int i = 0; i < 16; i++) { + output[out_offset + i * out_offset_add] = (FLOAT)0; + } + return; + } + + const int in_offset = (dst_c * srcChannel + src_c) * 9; + FLOAT8 in = CONVERT_FLOAT8(vload8(0, input + in_offset)); + FLOAT in8 = input[in_offset+8]; + + FLOAT GB_00 = in.s0; + FLOAT GB_01 = in.s1; + FLOAT GB_02 = in.s2; + FLOAT GB_10 = in.s0 + in.s3 + in.s6; + FLOAT GB_11 = in.s1 + in.s4 + in.s7; + FLOAT GB_12 = in.s2 + in.s5 + in8; + FLOAT GB_20 = in.s0 - in.s3 + in.s6; + FLOAT GB_21 = in.s1 - in.s4 + in.s7; + FLOAT GB_22 = in.s2 - in.s5 + in8; + FLOAT GB_30 = in.s6; + FLOAT GB_31 = in.s7; + FLOAT GB_32 = in8; + + FLOAT GBGT_00 = GB_00; + FLOAT GBGT_01 = GB_00 + GB_01 + GB_02; + FLOAT GBGT_02 = GB_00 - GB_01 + GB_02; + FLOAT GBGT_03 = GB_02; + + FLOAT GBGT_10 = GB_10; + FLOAT GBGT_11 = GB_10 + GB_11 + GB_12; + FLOAT GBGT_12 = GB_10 - GB_11 + GB_12; + FLOAT GBGT_13 = GB_12; + + FLOAT GBGT_20 = GB_20; + FLOAT GBGT_21 = GB_20 + GB_21 + GB_22; + FLOAT GBGT_22 = GB_20 - GB_21 + GB_22; + FLOAT GBGT_23 = GB_22; + + FLOAT GBGT_30 = GB_30; + FLOAT GBGT_31 = GB_30 + GB_31 + GB_32; + FLOAT GBGT_32 = GB_30 - GB_31 + GB_32; + FLOAT GBGT_33 = GB_32; + + output[out_offset + 0 * out_offset_add] = GBGT_00; + output[out_offset + 1 * out_offset_add] = GBGT_01; + output[out_offset + 2 * out_offset_add] = GBGT_02; + output[out_offset + 3 * out_offset_add] = GBGT_03; + output[out_offset + 4 * out_offset_add] = GBGT_10; + output[out_offset + 5 * out_offset_add] = GBGT_11; + output[out_offset + 6 * out_offset_add] = GBGT_12; + output[out_offset + 7 * out_offset_add] = GBGT_13; + output[out_offset + 8 * out_offset_add] = GBGT_20; + output[out_offset + 9 * out_offset_add] = GBGT_21; + output[out_offset + 10 * out_offset_add] = GBGT_22; + output[out_offset + 11 * out_offset_add] = GBGT_23; + output[out_offset + 12 * out_offset_add] = GBGT_30; + output[out_offset + 13 * out_offset_add] = GBGT_31; + output[out_offset + 14 * out_offset_add] = GBGT_32; + output[out_offset + 15 * out_offset_add] = GBGT_33; +} + __kernel void winoTransSrcBuf2_3_1(GLOBAL_SIZE_DIM2 __global const FLOAT* uInput, // 0 __global FLOAT* uOutput, __private const int unitWidth, @@ -17,10 +96,14 @@ __kernel void winoTransSrcBuf2_3_1(GLOBAL_SIZE_DIM2 __private const int padX, __private const int padY, __private const int srcWidth, // 6 __private const int srcHeight, __private const int srcChannelC4, + __private const int dstHeightPad, __private const int srcChannelPad, __private const int batchOffset) { int2 pos = (int2)(get_global_id(0), get_global_id(1)); UNIFORM_BOUNDRY_CHECK(pos.x, pos.y); + if(pos.x >= unitWidth * unitHeight || pos.y >= srcChannelC4) { + return; + } int unitWidth_idx = pos.x % unitWidth; int unitHeight_idx = pos.x / unitWidth; int2 realPos = (int2)(unitWidth_idx, unitHeight_idx); @@ -183,26 +266,123 @@ __kernel void winoTransSrcBuf2_3_1(GLOBAL_SIZE_DIM2 FLOAT4 m23 = -S21 + S23; FLOAT4 m33 = -S31 + S33; - //NC4HW4 [alpha*alpha, srcChannelC4, dstHeight, 4] + //NC4HW4 [alpha*alpha, srcChannelPad, dstHeightPad] //index: [0, dstXOrigin, dstY, dstYOrigin % 4] - int out_offset = (((0*srcChannelC4 + dstXOrigin) * dstHeight + dstY) * 4 + dstYOrigin % 4)*4; - int batch_offset = srcChannelC4*dstHeight*16; - vstore4(+m00 - m20, 0, uOutput+out_offset+0*batch_offset); - vstore4(+(FLOAT)0.5f * m10 + (FLOAT)0.5f * m20, 0, uOutput+out_offset+1*batch_offset); - vstore4(-(FLOAT)0.5f * m10 + (FLOAT)0.5f * m20, 0, uOutput+out_offset+2*batch_offset); - vstore4(-m10 + m30, 0, uOutput+out_offset+3*batch_offset); - vstore4(+m01 - m21, 0, uOutput+out_offset+4*batch_offset); - vstore4(+(FLOAT)0.5f * m11 + (FLOAT)0.5f * m21, 0, uOutput+out_offset+5*batch_offset); - vstore4(-(FLOAT)0.5f * m11 + (FLOAT)0.5f * m21, 0, uOutput+out_offset+6*batch_offset); - vstore4(-m11 + m31, 0, uOutput+out_offset+7*batch_offset); - vstore4(+m02 - m22, 0, uOutput+out_offset+8*batch_offset); - vstore4(+(FLOAT)0.5f * m12 + (FLOAT)0.5f * m22, 0, uOutput+out_offset+9*batch_offset); - vstore4(-(FLOAT)0.5f * m12 + (FLOAT)0.5f * m22, 0, uOutput+out_offset+10*batch_offset); - vstore4(-m12 + m32, 0, uOutput+out_offset+11*batch_offset); - vstore4(+m03 - m23, 0, uOutput+out_offset+12*batch_offset); - vstore4(+(FLOAT)0.5f * m13 + (FLOAT)0.5f * m23, 0, uOutput+out_offset+13*batch_offset); - vstore4(-(FLOAT)0.5f * m13 + (FLOAT)0.5f * m23, 0, uOutput+out_offset+14*batch_offset); - vstore4(-m13 + m33, 0, uOutput+out_offset+15*batch_offset); + + int out_offset = (0*srcChannelPad + 4*dstXOrigin) * dstHeightPad + dstYOrigin; + int batch_offset = srcChannelPad*dstHeightPad; + + FLOAT4 res = (+m00 - m20); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (+(FLOAT)0.5f * m10 + (FLOAT)0.5f * m20); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-(FLOAT)0.5f * m10 + (FLOAT)0.5f * m20); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-m10 + m30); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + + out_offset += batch_offset; + res = (+m01 - m21); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (+(FLOAT)0.5f * m11 + (FLOAT)0.5f * m21); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-(FLOAT)0.5f * m11 + (FLOAT)0.5f * m21); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-m11 + m31); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (+m02 - m22); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (+(FLOAT)0.5f * m12 + (FLOAT)0.5f * m22); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-(FLOAT)0.5f * m12 + (FLOAT)0.5f * m22); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-m12 + m32); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (+m03 - m23); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (+(FLOAT)0.5f * m13 + (FLOAT)0.5f * m23); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-(FLOAT)0.5f * m13 + (FLOAT)0.5f * m23); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; + + out_offset += batch_offset; + res = (-m13 + m33); + uOutput[out_offset] = res.x; + uOutput[out_offset + dstHeightPad] = res.y; + uOutput[out_offset + dstHeightPad + dstHeightPad] = res.z; + uOutput[out_offset + dstHeightPad + dstHeightPad + dstHeightPad] = res.w; } } @@ -216,6 +396,8 @@ __kernel void winoTransDstBuf2_3_1(GLOBAL_SIZE_DIM2 __private const int dstWidth, __private const int dstHeight, __private const int dstChannelC4, + __private const int srcWidthPad, + __private const int dstChannelPad, __private const int batchOffset) { int2 pos = (int2)(get_global_id(0), get_global_id(1)); UNIFORM_BOUNDRY_CHECK(pos.x, pos.y); @@ -237,26 +419,28 @@ __kernel void winoTransDstBuf2_3_1(GLOBAL_SIZE_DIM2 int oyStart = realPos.y * 2; int oxStart = realPos.x * 2; - //NC4HW4 [dstChannelC4, alpha2, 4, UP_DIV(wUnit*hUnit,4)] x 4 - //index: [pos.y, 0, dstXOrigin % 4, dstX] - const int inp_offset = (((pos.y * 16 + 0) * 4 + dstXOrigin % 4) * srcWidth + dstX) * 4; - const int ic_offset = 16*srcWidth; - FLOAT4 S00 = vload4(0, uInput+inp_offset+ic_offset*0); - FLOAT4 S10 = vload4(0, uInput+inp_offset+ic_offset*1); - FLOAT4 S20 = vload4(0, uInput+inp_offset+ic_offset*2); - FLOAT4 S30 = vload4(0, uInput+inp_offset+ic_offset*3); - FLOAT4 S01 = vload4(0, uInput+inp_offset+ic_offset*4); - FLOAT4 S11 = vload4(0, uInput+inp_offset+ic_offset*5); - FLOAT4 S21 = vload4(0, uInput+inp_offset+ic_offset*6); - FLOAT4 S31 = vload4(0, uInput+inp_offset+ic_offset*7); - FLOAT4 S02 = vload4(0, uInput+inp_offset+ic_offset*8); - FLOAT4 S12 = vload4(0, uInput+inp_offset+ic_offset*9); - FLOAT4 S22 = vload4(0, uInput+inp_offset+ic_offset*10); - FLOAT4 S32 = vload4(0, uInput+inp_offset+ic_offset*11); - FLOAT4 S03 = vload4(0, uInput+inp_offset+ic_offset*12); - FLOAT4 S13 = vload4(0, uInput+inp_offset+ic_offset*13); - FLOAT4 S23 = vload4(0, uInput+inp_offset+ic_offset*14); - FLOAT4 S33 = vload4(0, uInput+inp_offset+ic_offset*15); + // [alpha2, srcWidthPad, dstChannelPad] + //index: [0, dstXOrigin, 4*oz] + + const int inp_offset = (0 * srcWidthPad + dstXOrigin) * dstChannelPad + 4*oz; + const int b_offset = dstChannelPad*srcWidthPad; + + FLOAT4 S00 = vload4(0, uInput+inp_offset+b_offset*0); + FLOAT4 S10 = vload4(0, uInput+inp_offset+b_offset*1); + FLOAT4 S20 = vload4(0, uInput+inp_offset+b_offset*2); + FLOAT4 S30 = vload4(0, uInput+inp_offset+b_offset*3); + FLOAT4 S01 = vload4(0, uInput+inp_offset+b_offset*4); + FLOAT4 S11 = vload4(0, uInput+inp_offset+b_offset*5); + FLOAT4 S21 = vload4(0, uInput+inp_offset+b_offset*6); + FLOAT4 S31 = vload4(0, uInput+inp_offset+b_offset*7); + FLOAT4 S02 = vload4(0, uInput+inp_offset+b_offset*8); + FLOAT4 S12 = vload4(0, uInput+inp_offset+b_offset*9); + FLOAT4 S22 = vload4(0, uInput+inp_offset+b_offset*10); + FLOAT4 S32 = vload4(0, uInput+inp_offset+b_offset*11); + FLOAT4 S03 = vload4(0, uInput+inp_offset+b_offset*12); + FLOAT4 S13 = vload4(0, uInput+inp_offset+b_offset*13); + FLOAT4 S23 = vload4(0, uInput+inp_offset+b_offset*14); + FLOAT4 S33 = vload4(0, uInput+inp_offset+b_offset*15); FLOAT4 m00 = +S00 + S01 + S02; FLOAT4 m10 = +S10 + S11 + S12; diff --git a/source/backend/opencl/execution/image/ConvExecution.cpp b/source/backend/opencl/execution/image/ConvExecution.cpp index 74673a469..f83de1223 100644 --- a/source/backend/opencl/execution/image/ConvExecution.cpp +++ b/source/backend/opencl/execution/image/ConvExecution.cpp @@ -187,9 +187,9 @@ ConvExecution::ConvExecution(const std::vector &inputs, const std::vec } mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(*(mResource->mKernelBuffer.get()), kernelBufferPtr); }else{ - std::vector filterImageShape{(int)inputChannel, (int)(UP_DIV(outputChannel, 4) * kernelWidth * kernelHeight)}; + std::vector filterImageShape{(int)ROUND_UP(inputChannel, 4), (int)(UP_DIV(outputChannel, 4) * kernelWidth * kernelHeight)}; std::shared_ptr filterBuffer( - Tensor::createDevice({outputChannel, inputChannel, kernelWidth, kernelHeight})); + Tensor::createDevice({outputChannel, ROUND_UP(inputChannel, 4), kernelWidth, kernelHeight})); size_t buffer_size = filterBuffer->elementSize() * sizeof(float); cl::Buffer filterBufferCL(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, buffer_size); @@ -199,7 +199,12 @@ ConvExecution::ConvExecution(const std::vector &inputs, const std::vec auto ptrCL = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(filterBufferCL, true, CL_MAP_WRITE, 0, buffer_size, nullptr, nullptr, &error); if(ptrCL != nullptr && error == CL_SUCCESS) { ::memset(ptrCL, 0, buffer_size); - ::memcpy(ptrCL, filterDataPtr, filterBuffer->size()); + int cpySrcNum = inputChannel * kernelWidth * kernelHeight; + int cpyDstNum = ROUND_UP(inputChannel, 4) * kernelWidth * kernelHeight; + int cpysize = cpySrcNum * sizeof(float); + for(int o = 0; o < outputChannel; ++o){ + ::memcpy((float*)ptrCL + o * cpyDstNum, filterDataPtr + o * cpySrcNum, cpysize); + } }else{ MNN_ERROR("Map error ptrCL == nullptr \n"); @@ -322,7 +327,7 @@ ErrorCode ConvExecution::onEncode(const std::vector &inputs, const std std::vector localWorkSize[total_kernel]; std::pair min_cost(INT_MAX, 0);//(min_time, min_index) - for(int knl_idx = 0; knl_idx < total_kernel; knl_idx++) { + for(int knl_idx = 0; knl_idx < 1; knl_idx++) { kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d", kernelName[knl_idx], mResource->mBuildOptions); uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); @@ -488,15 +493,18 @@ class ConvolutionCreator : public OpenCLBackend::Creator { #if defined(MNN_LOW_MEMORY) && not defined(MNN_OPENCL_BUFFER_CLOSED) { auto conv2dParams = op->main_as_Convolution2D(); - if ((static_cast(backend)->getMemory() == BackendConfig::Memory_Low) && (conv2dParams->quanParameter() != nullptr)) { + if (conv2dParams->quanParameter() != nullptr) { if (((conv2dParams->quanParameter()->type() == 4) || (conv2dParams->quanParameter()->type() == 1) || (conv2dParams->quanParameter()->type() == 2))) { - // Todo: support int4 inputchannel % 4 not equal 4 + if ((1 == conv2dParams->quanParameter()->type() || 2 == conv2dParams->quanParameter()->type()) && conv2dParams->quanParameter()->has_scaleInt()) { + // Don't support IDST-int8 because of error + return nullptr; + } return new ConvLowMemoryExecution(inputs, outputs, op, backend); } else { - MNN_ERROR("OpenCL Conv buf low memory init error. For Opencl Backend, only support low memory mode of int8 or int4 dequantization currently.\n"); - MNN_ASSERT(false); + //MNN_ERROR("OpenCL Conv buf low memory init error. For Opencl Backend, only support low memory mode of int8 or int4 dequantization currently.\n"); + return nullptr; } } } diff --git a/source/backend/opencl/execution/image/ConvExecution.hpp b/source/backend/opencl/execution/image/ConvExecution.hpp index 537a8aec2..2e68a5e41 100644 --- a/source/backend/opencl/execution/image/ConvExecution.hpp +++ b/source/backend/opencl/execution/image/ConvExecution.hpp @@ -27,8 +27,7 @@ struct ConvResource { std::shared_ptr mFilter; std::shared_ptr mBias; std::shared_ptr mKernelBuffer; - std::shared_ptr dequantScaleBuffer; - std::shared_ptr dequantOffsetBuffer; + std::shared_ptr dequantScaleOffset; std::vector mStrides{1, 1}; std::vector mDilations{1, 1}; std::set mBuildOptions; @@ -36,6 +35,7 @@ struct ConvResource { bool mConv1x1Opt = false; bool mWeightUseBuffer = false; bool gemmOpt = false; + int mBlockSize; int mKernelWidth; int mKernelHeight; int mOutputChannel; diff --git a/source/backend/opencl/execution/image/ConvLowMemoryExecution.cpp b/source/backend/opencl/execution/image/ConvLowMemoryExecution.cpp index cf9fc07fa..830e6737d 100644 --- a/source/backend/opencl/execution/image/ConvLowMemoryExecution.cpp +++ b/source/backend/opencl/execution/image/ConvLowMemoryExecution.cpp @@ -13,56 +13,53 @@ namespace OpenCL { // set mDequantScale mDequantOffset mNumQuantBit mFilterDataPtr from mConv2dParams void ConvLowMemoryExecution::getInfoFromOpLowMemory(std::shared_ptr & quanCommon) { quanCommon = ConvolutionCommon::load(mResource->mConv2dParams, this->backend(), false, true); - if ((mOpenCLBackend->getMemory() == BackendConfig::Memory_Low) && (mResource->mConv2dParams->quanParameter() != nullptr)) { + if (mResource->mConv2dParams->quanParameter() != nullptr) { mLowMemoryFlag = true; } else { MNN_ERROR("Conv buf low memory init error.\n"); MNN_ASSERT(false); } + + mResource->mInputChannel = quanCommon->weight.size() / (mResource->mKernelWidth * mResource->mKernelHeight * mResource->mOutputChannel); // set mNumQuantBit - if (quanCommon->quan->type() == 4) { - mNumQuantBit = 8; - } else if (quanCommon->quan->type() == 1 || quanCommon->quan->type() == 2) { + if(quanCommon->canUseInt4){ mNumQuantBit = 4; - } else {/* More types to be supported. */} + }else{ + mNumQuantBit = 8; + } // src of alpha in CPU float * dequantAlpha = quanCommon->alpha.get(); + int totalCount = quanCommon->alpha.size(); + if (quanCommon->asymmetric) { + totalCount /= 2; + } int numAlpha = mResource->mOutputChannel; + mResource->mBlockSize = totalCount / numAlpha; // set mDequantScale mDequantOffset int numAlphaPack = ROUND_UP(numAlpha, 16); - int bytes = mOpenCLBackend->fpBytes(); - mResource->dequantScaleBuffer.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, numAlphaPack * bytes)); - mResource->dequantOffsetBuffer.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, numAlphaPack * bytes)); + int mapSize = mResource->mBlockSize * numAlphaPack * sizeof(int32_t) * 2; + mResource->dequantScaleOffset.reset(new cl::Buffer(mOpenCLBackend->getOpenCLRuntime()->context(), CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, mapSize)); // transfer data from src in cpu to dst in gpu - cl_int resBias, resScale, resOffset; - void * dequantScaleBufferMap = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(*(mResource->dequantScaleBuffer.get()), true, CL_MAP_WRITE, 0, numAlphaPack * bytes, nullptr, nullptr, &resScale); - void * dequantOffsetBufferMap = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(*(mResource->dequantOffsetBuffer.get()), true, CL_MAP_WRITE, 0, numAlphaPack * bytes, nullptr, nullptr, &resOffset); - - ::memset(dequantScaleBufferMap, -1, numAlphaPack * bytes); - ::memset(dequantOffsetBufferMap, 0, numAlphaPack * bytes); - if (dequantScaleBufferMap != nullptr && dequantOffsetBufferMap != nullptr && resScale == CL_SUCCESS && resOffset == CL_SUCCESS) { - if (bytes == 2) { - if (quanCommon->asymmetric) { - for (int i = 0; i < numAlpha; ++i) { - ((half_float::half *)dequantOffsetBufferMap)[i] = (half_float::half)dequantAlpha[2 * i]; - ((half_float::half *)dequantScaleBufferMap)[i] = (half_float::half)dequantAlpha[2 * i + 1]; - } - } else { - for (int i = 0; i < numAlpha; ++i) { - ((half_float::half *)dequantScaleBufferMap)[i] = (half_float::half)dequantAlpha[i]; - ((half_float::half *)dequantOffsetBufferMap)[i] = 0.0f; + cl_int resScaleOffset; + void * dequantScaleOffsetBufferMap = mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueMapBuffer(*mResource->dequantScaleOffset.get(), true, CL_MAP_WRITE, 0, mapSize, nullptr, nullptr, &resScaleOffset); + // mBlockSize % 4 need equal 0 + if (dequantScaleOffsetBufferMap != nullptr && resScaleOffset == CL_SUCCESS) { + if (quanCommon->asymmetric) { + for (int i = 0; i < numAlpha; ++i) { + auto srcZ = dequantAlpha + i * mResource->mBlockSize * 2; + for(int j = 0; j < mResource->mBlockSize; ++j){ + float o = srcZ[2*j+0]; + float s = srcZ[2*j+1]; + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2] = s; + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2 + 1] = o; } } } else { - if (quanCommon->asymmetric) { - for (int i = 0; i < numAlpha; ++i) { - ((float *)dequantOffsetBufferMap)[i] = dequantAlpha[2 * i]; - ((float *)dequantScaleBufferMap)[i] = dequantAlpha[2 * i + 1]; - } - } else { - for (int i = 0; i < numAlpha; ++i) { - ((float *)dequantScaleBufferMap)[i] = dequantAlpha[i]; - ((float *)dequantOffsetBufferMap)[i] = 0.0f; + for (int i = 0; i < numAlpha; ++i) { + auto srcZ = dequantAlpha + i * mResource->mBlockSize; + for(int j = 0; j < mResource->mBlockSize; ++j){ + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2] = srcZ[j]; + ((float *)dequantScaleOffsetBufferMap)[(j * numAlphaPack + i) * 2 + 1] = 0.0f; } } } @@ -70,8 +67,7 @@ void ConvLowMemoryExecution::getInfoFromOpLowMemory(std::shared_ptrgetOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(*(mResource->dequantScaleBuffer.get()), dequantScaleBufferMap); - mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(*(mResource->dequantOffsetBuffer.get()), dequantOffsetBufferMap); + mOpenCLBackend->getOpenCLRuntime()->commandQueue().enqueueUnmapMemObject(*mResource->dequantScaleOffset.get(), dequantScaleOffsetBufferMap); // set mFilterDataPtr mFilterDataPtr = (void *)quanCommon->weight.get(); } @@ -96,10 +92,6 @@ void ConvLowMemoryExecution::set1x1WeightLowMemory(int packCout, int packCin, vo for(int o = 0; o < mResource->mOutputChannel; o++){ - float zero = 0; - if(quanCommon->asymmetric){ - zero = (-dequantAlpha[2 * o + 1])/dequantAlpha[2 * o]; - } int i = 0; for(; i < mResource->mInputChannel; i++){ int bufferIdx = (o/packCout) * packCin*packCout + (i/packCin)*packCin*ROUND_UP(mResource->mOutputChannel, packCout) + (i%packCin)*packCout + (o%packCout);//(Ci/packCin， Co/packCout, packCin， packCout) @@ -116,20 +108,6 @@ void ConvLowMemoryExecution::set1x1WeightLowMemory(int packCout, int packCin, vo } } else {/* More types to be supported. */} } - for(; i < ROUND_UP(mResource->mInputChannel, 4); i++){ - int bufferIdx = (o/packCout) * packCin*packCout + (i/packCin)*packCin*ROUND_UP(mResource->mOutputChannel, packCout) + (i%packCin)*packCout + (o%packCout);//(Ci/packCin， Co/packCout, packCin， packCout) - if (mNumQuantBit == 8) { - // int8 case - ((int8_t *)kernelBufferPtr)[bufferIdx] = (int8_t)(zero); - } else if (mNumQuantBit == 4){ - // int4 case - if (bufferIdx % 2 == 0) { - ((uint8_t *)kernelBufferPtr)[bufferIdx / 2] += (uint8_t)((zero + 8) * 16); - } else { - ((uint8_t *)kernelBufferPtr)[bufferIdx / 2] += (uint8_t)(zero + 8); - } - } - } } } else { MNN_ERROR("set1x1WeightLowMemory: Map error ptrCL == nullptr \n"); @@ -155,17 +133,10 @@ void ConvLowMemoryExecution::setGeneralWeightLowMemory(void* filterDataPtr, std: ::memset(ptrCL, 0, buffer_size); const int copy_size = mResource->mKernelWidth * mResource->mKernelHeight * sizeof(int8_t); for(int oc=0; ocmOutputChannel; oc++) { - float zero = 0; - if(quanCommon->asymmetric){ - zero = (-dequantAlpha[2 * oc + 1])/dequantAlpha[2 * oc]; - } int ic = 0; for(; icmInputChannel; ic++) { ::memcpy((int8_t *)ptrCL + (oc * ROUND_UP(mResource->mInputChannel, 4) + ic) * mResource->mKernelWidth * mResource->mKernelHeight, ((int8_t *)filterDataPtr) + (oc * mResource->mInputChannel + ic) * mResource->mKernelWidth * mResource->mKernelHeight, copy_size); } - for(; icmInputChannel, 4); ic++) { - ((int8_t *)ptrCL)[(oc * ROUND_UP(mResource->mInputChannel, 4) + ic) * mResource->mKernelWidth * mResource->mKernelHeight] = (int8_t)(zero); - } } } else { MNN_ERROR("setGeneralWeightLowMemory: Map error ptrCL == nullptr \n"); @@ -210,6 +181,7 @@ void ConvLowMemoryExecution::tune1x1CaseLowMemory(Tensor * input, Tensor * outpu const int inputWidth = inputShape.at(2); const int inputChannels = inputShape.at(3); const int inputChannelBlocks = UP_DIV(inputChannels, 4); + const int blockDim = mResource->mInputChannel / mResource->mBlockSize; std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel) + "_" + std::to_string(mResource->mKernelHeight) + "_" + std::to_string(mResource->mKernelWidth) + "_" + std::to_string(mResource->mStrides[0]) + "_" + std::to_string(mResource->mStrides[1]) + "_" + std::to_string(mResource->mDilations[0]) + "_" + std::to_string(mResource->mDilations[1]); int inputImageShape[2] = {inputHeight, inputWidth}; int outputImageShape[2] = {height, width}; @@ -228,6 +200,9 @@ void ConvLowMemoryExecution::tune1x1CaseLowMemory(Tensor * input, Tensor * outpu cl_int ret = CL_SUCCESS; for(int knl_idx = 0; knl_idx < actual_kernel; knl_idx++) { std::set buildOption = mResource->mBuildOptions; + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d", kernelName[knl_idx], buildOption); uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); @@ -237,8 +212,7 @@ void ConvLowMemoryExecution::tune1x1CaseLowMemory(Tensor * input, Tensor * outpu ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][1]); ret |= kernel[knl_idx]->get().setArg(idx++, openCLImage(input)); ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->mKernelBuffer.get()); - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->dequantScaleBuffer.get()); - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->dequantOffsetBuffer.get()); + ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->dequantScaleOffset.get()); ret |= kernel[knl_idx]->get().setArg(idx++, openCLImage(mResource->mBias.get())); ret |= kernel[knl_idx]->get().setArg(idx++, openCLImage(output)); ret |= kernel[knl_idx]->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); @@ -247,6 +221,8 @@ void ConvLowMemoryExecution::tune1x1CaseLowMemory(Tensor * input, Tensor * outpu ret |= kernel[knl_idx]->get().setArg(idx++, sizeof(stideShape), stideShape); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(width, 4)); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(outputShape.at(3), 4)); + ret |= kernel[knl_idx]->get().setArg(idx++, blockDim); + ret |= kernel[knl_idx]->get().setArg(idx++, inputChannels); std::pair, uint32_t> retTune; retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); @@ -262,14 +238,16 @@ void ConvLowMemoryExecution::tune1x1CaseLowMemory(Tensor * input, Tensor * outpu int min_index = min_cost.second; mGlobalWorkSize = {globalWorkSize[min_index][0], globalWorkSize[min_index][1]}; std::set buildOption = mResource->mBuildOptions; + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d", kernelName[min_index], buildOption); uint32_t idx = 0; ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[0]); ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); ret |= unit.kernel->get().setArg(idx++, openCLImage(input)); ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); - ret |= unit.kernel->get().setArg(idx++, *mResource->dequantScaleBuffer.get()); - ret |= unit.kernel->get().setArg(idx++, *mResource->dequantOffsetBuffer.get()); + ret |= unit.kernel->get().setArg(idx++, *mResource->dequantScaleOffset.get()); ret |= unit.kernel->get().setArg(idx++, openCLImage(mResource->mBias.get())); ret |= unit.kernel->get().setArg(idx++, openCLImage(output)); ret |= unit.kernel->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); @@ -278,6 +256,8 @@ void ConvLowMemoryExecution::tune1x1CaseLowMemory(Tensor * input, Tensor * outpu ret |= unit.kernel->get().setArg(idx++, sizeof(stideShape), stideShape); ret |= unit.kernel->get().setArg(idx++, UP_DIV(width, 4)); ret |= unit.kernel->get().setArg(idx++, UP_DIV(outputShape.at(3), 4)); + ret |= unit.kernel->get().setArg(idx++, blockDim); + ret |= unit.kernel->get().setArg(idx++, inputChannels); MNN_CHECK_CL_SUCCESS(ret, "setArg Conv1x1LowMemory"); mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); @@ -298,6 +278,7 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o const int inputWidth = inputShape.at(2); const int inputChannels = inputShape.at(3); const int inputChannelBlocks = UP_DIV(inputChannels, 4); + const int blockDim = mResource->mInputChannel / mResource->mBlockSize; std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel) + "_" + std::to_string(mResource->mKernelHeight) + "_" + std::to_string(mResource->mKernelWidth) + "_" + std::to_string(mResource->mStrides[0]) + "_" + std::to_string(mResource->mStrides[1]) + "_" + std::to_string(mResource->mDilations[0]) + "_" + std::to_string(mResource->mDilations[1]); int inputImageShape[2] = {inputHeight, inputWidth}; int outputImageShape[2] = {height, width}; @@ -318,6 +299,9 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o // MNN_PRINT("Checking kernel %d.\n", knlCheck); for (int knl_idx = 0; knl_idx < actual_kernel; knl_idx++) { std::set buildOption = mResource->mBuildOptions; + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } kernel[knl_idx] = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d", kernelName[knl_idx], buildOption); uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(kernel[knl_idx])); @@ -328,8 +312,7 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o ret |= kernel[knl_idx]->get().setArg(idx++, globalWorkSize[knl_idx][1]); ret |= kernel[knl_idx]->get().setArg(idx++, openCLImage(input)); ret |= kernel[knl_idx]->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->dequantScaleBuffer.get()); - ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->dequantOffsetBuffer.get()); + ret |= kernel[knl_idx]->get().setArg(idx++, *mResource->dequantScaleOffset.get()); ret |= kernel[knl_idx]->get().setArg(idx++, openCLImage(mResource->mBias.get())); ret |= kernel[knl_idx]->get().setArg(idx++, openCLImage(output)); ret |= kernel[knl_idx]->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); @@ -342,6 +325,8 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(width, itemW[knl_idx])); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(outputShape.at(3), 4)); ret |= kernel[knl_idx]->get().setArg(idx++, UP_DIV(height, itemH[knl_idx])); + ret |= kernel[knl_idx]->get().setArg(idx++, blockDim); + ret |= kernel[knl_idx]->get().setArg(idx++, inputChannels); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvLowMemory Kernel Select"); std::pair, int> retTune; retTune = localWS2DDefault(globalWorkSize[knl_idx], maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelName[knl_idx] + info, kernel[knl_idx]); @@ -355,6 +340,9 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o mGlobalWorkSize = {globalWorkSize[min_index][0], globalWorkSize[min_index][1]}; std::set buildOption = mResource->mBuildOptions; + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("conv_2d", kernelName[min_index], buildOption); uint32_t idx = 0; @@ -363,8 +351,7 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); ret |= unit.kernel->get().setArg(idx++, openCLImage(input)); ret |= unit.kernel->get().setArg(idx++, openCLBuffer(mResource->mFilter.get())); - ret |= unit.kernel->get().setArg(idx++, *mResource->dequantScaleBuffer.get()); - ret |= unit.kernel->get().setArg(idx++, *mResource->dequantOffsetBuffer.get()); + ret |= unit.kernel->get().setArg(idx++, *mResource->dequantScaleOffset.get()); ret |= unit.kernel->get().setArg(idx++, openCLImage(mResource->mBias.get())); ret |= unit.kernel->get().setArg(idx++, openCLImage(output)); ret |= unit.kernel->get().setArg(idx++, sizeof(inputImageShape), inputImageShape); @@ -377,6 +364,8 @@ void ConvLowMemoryExecution::tuneGeneralCaseLowMemory(Tensor * input, Tensor * o ret |= unit.kernel->get().setArg(idx++, UP_DIV(width, itemW[min_index])); ret |= unit.kernel->get().setArg(idx++, UP_DIV(outputShape.at(3), 4)); ret |= unit.kernel->get().setArg(idx++, UP_DIV(height, itemH[min_index])); + ret |= unit.kernel->get().setArg(idx++, blockDim); + ret |= unit.kernel->get().setArg(idx++, inputChannels); MNN_CHECK_CL_SUCCESS(ret, "setArg ConvLowMemory"); mOpenCLBackend->recordKernel2d(unit.kernel, mGlobalWorkSize, mLocalWorkSize); @@ -394,6 +383,7 @@ void ConvLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * output) const int batch = outputShape.at(0); const int inputChannelBlocks = UP_DIV(inputChannels, 4); const int outputChannelBlocks = UP_DIV(outChannel, 4); + const int blockDim = mResource->mInputChannel / mResource->mBlockSize; std::string kernelname = "gemm_conv"; int global_x = outputChannelBlocks; int global_y = batch; @@ -403,7 +393,11 @@ void ConvLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * output) global_y = UP_DIV(batch, 2); } std::string info = std::to_string(inputChannels) + "_" + std::to_string(outChannel); - unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm", kernelname, mResource->mBuildOptions); + std::set buildOption = mResource->mBuildOptions; + if(inputChannels % 4 != 0){ + buildOption.emplace("-DINPUT_CHANNEL_LEAVE"); + } + unit.kernel = mOpenCLBackend->getOpenCLRuntime()->buildKernel("gemm", kernelname, buildOption); uint32_t maxWorkGroupSize = static_cast(mOpenCLBackend->getOpenCLRuntime()->getMaxWorkGroupSize(unit.kernel)); mGlobalWorkSize = {static_cast(global_x), static_cast(global_y)}; // MNN_PRINT("Kernel is %d.\n", min_index); @@ -413,13 +407,14 @@ void ConvLowMemoryExecution::tuneGemmLowMemory(Tensor * input, Tensor * output) ret |= unit.kernel->get().setArg(idx++, mGlobalWorkSize[1]); ret |= unit.kernel->get().setArg(idx++, openCLImage(input)); ret |= unit.kernel->get().setArg(idx++, *mResource->mKernelBuffer.get()); - ret |= unit.kernel->get().setArg(idx++, *mResource->dequantScaleBuffer.get()); - ret |= unit.kernel->get().setArg(idx++, *mResource->dequantOffsetBuffer.get()); + ret |= unit.kernel->get().setArg(idx++, *mResource->dequantScaleOffset.get()); ret |= unit.kernel->get().setArg(idx++, openCLImage(mResource->mBias.get())); ret |= unit.kernel->get().setArg(idx++, openCLImage(output)); ret |= unit.kernel->get().setArg(idx++, static_cast(outputChannelBlocks)); ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannelBlocks)); ret |= unit.kernel->get().setArg(idx++, static_cast(batch)); + ret |= unit.kernel->get().setArg(idx++, static_cast(blockDim)); + ret |= unit.kernel->get().setArg(idx++, static_cast(inputChannels)); MNN_CHECK_CL_SUCCESS(ret, "setArg gemm_conv"); mLocalWorkSize = localWS2DDefault(mGlobalWorkSize, maxWorkGroupSize, mOpenCLBackend->getOpenCLRuntime(), kernelname + info, unit.kernel).first; @@ -449,16 +444,16 @@ ConvLowMemoryExecution::ConvLowMemoryExecution(const std::vector &inpu mResource->mKernelWidth = conv2dCommonParams->kernelX(); mResource->mKernelHeight = conv2dCommonParams->kernelY(); mResource->mOutputChannel = conv2dCommonParams->outputCount(); - mResource->mInputChannel = conv2dCommonParams->inputCount(); std::shared_ptr quanCommon; // set mDequantScale, mDequantOffset, mFilterDataPtr // prepare mDequantScale mDequantOffset mFilterDataPtr getInfoFromOpLowMemory(quanCommon); //select opt conv method - if (mResource->mKernelHeight == mResource->mKernelWidth && mResource->mKernelHeight == 1 && mResource->mStrides[0] == 1 && mResource->mStrides[1] == 1) { + if (mResource->mKernelHeight == mResource->mKernelWidth && mResource->mKernelHeight == 1 && mResource->mStrides[0] == 1 && mResource->mStrides[1] == 1 && mPaddings[0] == 0 && mPaddings[1] == 0) { // set mKernelBuffer for 1x1 case // At first, set packCout equal to 4 set1x1WeightLowMemory(4, 4, mFilterDataPtr, quanCommon); + mResource->mConv1x1Opt = true; }else { // set mFilter for not 1x1 case setGeneralWeightLowMemory(mFilterDataPtr, quanCommon); @@ -516,12 +511,11 @@ ErrorCode ConvLowMemoryExecution::onEncode(const std::vector &inputs, auto padding = ConvolutionCommon::convolutionPad(input, output, mResource->mConv2dCommonParams); mPaddings[0] = padding.second;//padY mPaddings[1] = padding.first;//padX - mResource->gemmOpt = (mResource->mKernelHeight == mResource->mKernelWidth && mResource->mKernelHeight == 1 && mPaddings[0] == 0 && mPaddings[1] == 0 && mResource->mStrides[0] == 1 && mResource->mStrides[1] == 1 && inputs[0]->width() == 1 && inputs[0]->height() == 1); - mResource->mConv1x1Opt = (mResource->mKernelHeight == mResource->mKernelWidth && mResource->mKernelHeight == 1 && mPaddings[0] == 0 && mPaddings[1] == 0 && mResource->mStrides[0] == 1 && mResource->mStrides[1] == 1 && inputs[0]->width() >= 4); - if (mResource->mConv1x1Opt) { - tune1x1CaseLowMemory(input, output); - } else if(mResource->gemmOpt){ + mResource->gemmOpt = (mResource->mConv1x1Opt && inputs[0]->width() == 1 && inputs[0]->height() == 1); + if (mResource->gemmOpt) { tuneGemmLowMemory(input, output); + } else if(mResource->mConv1x1Opt){ + tune1x1CaseLowMemory(input, output); } else { tuneGeneralCaseLowMemory(input, output); } diff --git a/source/backend/opencl/execution/image/RasterExecution.cpp b/source/backend/opencl/execution/image/RasterExecution.cpp index 7b2c0109f..15cdb6235 100644 --- a/source/backend/opencl/execution/image/RasterExecution.cpp +++ b/source/backend/opencl/execution/image/RasterExecution.cpp @@ -42,15 +42,11 @@ ErrorCode RasterExecution::onEncode(const std::vector &____inputs, con bool cancombine = CanCombine(outputs); // Alloc Temp buffer auto bufferPool = ((OpenCLBackend *)backend())->getBufferPool(); - auto bufferUnitSize = runtime->isSupportedFP16() ? sizeof(half_float::half) : sizeof(float); - if(output->getType().code == halide_type_int || output->getType().code == halide_type_uint) { - if(output->getType().bits == 8){ - bufferUnitSize = 1; - } else if(output->getType().bits == 32){ - bufferUnitSize = 1; - } + if(output->getType().code == halide_type_float && runtime->isSupportedFP16()) { + mTempOutput = bufferPool->alloc(output->usize()/2); + }else{ + mTempOutput = bufferPool->alloc(output->usize()); } - mTempOutput = bufferPool->alloc(output->elementSize() * bufferUnitSize); bufferPool->recycle(mTempOutput); auto originNum = mTempInput.size(); diff --git a/source/backend/opencl/schema/CLCache.fbs b/source/backend/opencl/schema/CLCache.fbs index 5be19886d..d53ce263f 100644 --- a/source/backend/opencl/schema/CLCache.fbs +++ b/source/backend/opencl/schema/CLCache.fbs @@ -24,10 +24,16 @@ table Autotuning { timeCost:uint; } +table GemmInfo { + gemmSize:[uint]; + paramInfo:[uint]; +} + table Cache { programs:[Shader]; tunings:[Autotuning]; tuned:[OpInfo]; + gemm:[GemmInfo]; } root_type Cache; diff --git a/source/backend/opencl/schema/current/CLCache_generated.h b/source/backend/opencl/schema/current/CLCache_generated.h index 8b3fdbddf..5918d6049 100644 --- a/source/backend/opencl/schema/current/CLCache_generated.h +++ b/source/backend/opencl/schema/current/CLCache_generated.h @@ -20,6 +20,9 @@ struct ShaderT; struct Autotuning; struct AutotuningT; +struct GemmInfo; +struct GemmInfoT; + struct Cache; struct CacheT; @@ -31,6 +34,8 @@ inline const flatbuffers::TypeTable *ShaderTypeTable(); inline const flatbuffers::TypeTable *AutotuningTypeTable(); +inline const flatbuffers::TypeTable *GemmInfoTypeTable(); + inline const flatbuffers::TypeTable *CacheTypeTable(); struct TensorInfoT : public flatbuffers::NativeTable { @@ -350,11 +355,77 @@ inline flatbuffers::Offset CreateAutotuning( flatbuffers::Offset CreateAutotuning(flatbuffers::FlatBufferBuilder &_fbb, const AutotuningT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr); +struct GemmInfoT : public flatbuffers::NativeTable { + typedef GemmInfo TableType; + std::vector gemmSize; + std::vector paramInfo; + GemmInfoT() { + } +}; + +struct GemmInfo FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table { + typedef GemmInfoT NativeTableType; + static const flatbuffers::TypeTable *MiniReflectTypeTable() { + return GemmInfoTypeTable(); + } + const flatbuffers::Vector *gemmSize() const { + return GetPointer *>(4); + } + const flatbuffers::Vector *paramInfo() const { + return GetPointer *>(6); + } + bool Verify(flatbuffers::Verifier &verifier) const { + return VerifyTableStart(verifier) && + VerifyOffset(verifier, 4) && + verifier.VerifyVector(gemmSize()) && + VerifyOffset(verifier, 6) && + verifier.VerifyVector(paramInfo()) && + verifier.EndTable(); + } + GemmInfoT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const; + void UnPackTo(GemmInfoT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const; + static flatbuffers::Offset Pack(flatbuffers::FlatBufferBuilder &_fbb, const GemmInfoT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr); +}; + +struct GemmInfoBuilder { + flatbuffers::FlatBufferBuilder &fbb_; + flatbuffers::uoffset_t start_; + void add_gemmSize(flatbuffers::Offset> gemmSize) { + fbb_.AddOffset(4, gemmSize); + } + void add_paramInfo(flatbuffers::Offset> paramInfo) { + fbb_.AddOffset(6, paramInfo); + } + explicit GemmInfoBuilder(flatbuffers::FlatBufferBuilder &_fbb) + : fbb_(_fbb) { + start_ = fbb_.StartTable(); + } + GemmInfoBuilder &operator=(const GemmInfoBuilder &); + flatbuffers::Offset Finish() { + const auto end = fbb_.EndTable(start_); + auto o = flatbuffers::Offset(end); + return o; + } +}; + +inline flatbuffers::Offset CreateGemmInfo( + flatbuffers::FlatBufferBuilder &_fbb, + flatbuffers::Offset> gemmSize = 0, + flatbuffers::Offset> paramInfo = 0) { + GemmInfoBuilder builder_(_fbb); + builder_.add_paramInfo(paramInfo); + builder_.add_gemmSize(gemmSize); + return builder_.Finish(); +} + +flatbuffers::Offset CreateGemmInfo(flatbuffers::FlatBufferBuilder &_fbb, const GemmInfoT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr); + struct CacheT : public flatbuffers::NativeTable { typedef Cache TableType; std::vector> programs; std::vector> tunings; std::vector> tuned; + std::vector> gemm; CacheT() { } }; @@ -373,6 +444,9 @@ struct Cache FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table { const flatbuffers::Vector> *tuned() const { return GetPointer> *>(8); } + const flatbuffers::Vector> *gemm() const { + return GetPointer> *>(10); + } bool Verify(flatbuffers::Verifier &verifier) const { return VerifyTableStart(verifier) && VerifyOffset(verifier, 4) && @@ -384,6 +458,9 @@ struct Cache FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table { VerifyOffset(verifier, 8) && verifier.VerifyVector(tuned()) && verifier.VerifyVectorOfTables(tuned()) && + VerifyOffset(verifier, 10) && + verifier.VerifyVector(gemm()) && + verifier.VerifyVectorOfTables(gemm()) && verifier.EndTable(); } CacheT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const; @@ -403,6 +480,9 @@ struct CacheBuilder { void add_tuned(flatbuffers::Offset>> tuned) { fbb_.AddOffset(8, tuned); } + void add_gemm(flatbuffers::Offset>> gemm) { + fbb_.AddOffset(10, gemm); + } explicit CacheBuilder(flatbuffers::FlatBufferBuilder &_fbb) : fbb_(_fbb) { start_ = fbb_.StartTable(); @@ -419,8 +499,10 @@ inline flatbuffers::Offset CreateCache( flatbuffers::FlatBufferBuilder &_fbb, flatbuffers::Offset>> programs = 0, flatbuffers::Offset>> tunings = 0, - flatbuffers::Offset>> tuned = 0) { + flatbuffers::Offset>> tuned = 0, + flatbuffers::Offset>> gemm = 0) { CacheBuilder builder_(_fbb); + builder_.add_gemm(gemm); builder_.add_tuned(tuned); builder_.add_tunings(tunings); builder_.add_programs(programs); @@ -560,6 +642,35 @@ inline flatbuffers::Offset CreateAutotuning(flatbuffers::FlatBufferB _timeCost); } +inline GemmInfoT *GemmInfo::UnPack(const flatbuffers::resolver_function_t *_resolver) const { + auto _o = new GemmInfoT(); + UnPackTo(_o, _resolver); + return _o; +} + +inline void GemmInfo::UnPackTo(GemmInfoT *_o, const flatbuffers::resolver_function_t *_resolver) const { + (void)_o; + (void)_resolver; + { auto _e = gemmSize(); if (_e) { _o->gemmSize.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->gemmSize[_i] = _e->Get(_i); } } }; + { auto _e = paramInfo(); if (_e) { _o->paramInfo.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->paramInfo[_i] = _e->Get(_i); } } }; +} + +inline flatbuffers::Offset GemmInfo::Pack(flatbuffers::FlatBufferBuilder &_fbb, const GemmInfoT* _o, const flatbuffers::rehasher_function_t *_rehasher) { + return CreateGemmInfo(_fbb, _o, _rehasher); +} + +inline flatbuffers::Offset CreateGemmInfo(flatbuffers::FlatBufferBuilder &_fbb, const GemmInfoT *_o, const flatbuffers::rehasher_function_t *_rehasher) { + (void)_rehasher; + (void)_o; + struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const GemmInfoT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va; + auto _gemmSize = _o->gemmSize.size() ? _fbb.CreateVector(_o->gemmSize) : 0; + auto _paramInfo = _o->paramInfo.size() ? _fbb.CreateVector(_o->paramInfo) : 0; + return CLCache::CreateGemmInfo( + _fbb, + _gemmSize, + _paramInfo); +} + inline CacheT *Cache::UnPack(const flatbuffers::resolver_function_t *_resolver) const { auto _o = new CacheT(); UnPackTo(_o, _resolver); @@ -572,6 +683,7 @@ inline void Cache::UnPackTo(CacheT *_o, const flatbuffers::resolver_function_t * { auto _e = programs(); if (_e) { _o->programs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->programs[_i] = std::unique_ptr(_e->Get(_i)->UnPack(_resolver)); } } }; { auto _e = tunings(); if (_e) { _o->tunings.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->tunings[_i] = std::unique_ptr(_e->Get(_i)->UnPack(_resolver)); } } }; { auto _e = tuned(); if (_e) { _o->tuned.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->tuned[_i] = std::unique_ptr(_e->Get(_i)->UnPack(_resolver)); } } }; + { auto _e = gemm(); if (_e) { _o->gemm.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->gemm[_i] = std::unique_ptr(_e->Get(_i)->UnPack(_resolver)); } } }; } inline flatbuffers::Offset Cache::Pack(flatbuffers::FlatBufferBuilder &_fbb, const CacheT* _o, const flatbuffers::rehasher_function_t *_rehasher) { @@ -585,11 +697,13 @@ inline flatbuffers::Offset CreateCache(flatbuffers::FlatBufferBuilder &_f auto _programs = _o->programs.size() ? _fbb.CreateVector> (_o->programs.size(), [](size_t i, _VectorArgs *__va) { return CreateShader(*__va->__fbb, __va->__o->programs[i].get(), __va->__rehasher); }, &_va ) : 0; auto _tunings = _o->tunings.size() ? _fbb.CreateVector> (_o->tunings.size(), [](size_t i, _VectorArgs *__va) { return CreateAutotuning(*__va->__fbb, __va->__o->tunings[i].get(), __va->__rehasher); }, &_va ) : 0; auto _tuned = _o->tuned.size() ? _fbb.CreateVector> (_o->tuned.size(), [](size_t i, _VectorArgs *__va) { return CreateOpInfo(*__va->__fbb, __va->__o->tuned[i].get(), __va->__rehasher); }, &_va ) : 0; + auto _gemm = _o->gemm.size() ? _fbb.CreateVector> (_o->gemm.size(), [](size_t i, _VectorArgs *__va) { return CreateGemmInfo(*__va->__fbb, __va->__o->gemm[i].get(), __va->__rehasher); }, &_va ) : 0; return CLCache::CreateCache( _fbb, _programs, _tunings, - _tuned); + _tuned, + _gemm); } inline const flatbuffers::TypeTable *TensorInfoTypeTable() { @@ -665,24 +779,42 @@ inline const flatbuffers::TypeTable *AutotuningTypeTable() { return &tt; } +inline const flatbuffers::TypeTable *GemmInfoTypeTable() { + static const flatbuffers::TypeCode type_codes[] = { + { flatbuffers::ET_UINT, 1, -1 }, + { flatbuffers::ET_UINT, 1, -1 } + }; + static const char * const names[] = { + "gemmSize", + "paramInfo" + }; + static const flatbuffers::TypeTable tt = { + flatbuffers::ST_TABLE, 2, type_codes, nullptr, nullptr, names + }; + return &tt; +} + inline const flatbuffers::TypeTable *CacheTypeTable() { static const flatbuffers::TypeCode type_codes[] = { { flatbuffers::ET_SEQUENCE, 1, 0 }, { flatbuffers::ET_SEQUENCE, 1, 1 }, - { flatbuffers::ET_SEQUENCE, 1, 2 } + { flatbuffers::ET_SEQUENCE, 1, 2 }, + { flatbuffers::ET_SEQUENCE, 1, 3 } }; static const flatbuffers::TypeFunction type_refs[] = { ShaderTypeTable, AutotuningTypeTable, - OpInfoTypeTable + OpInfoTypeTable, + GemmInfoTypeTable }; static const char * const names[] = { "programs", "tunings", - "tuned" + "tuned", + "gemm" }; static const flatbuffers::TypeTable tt = { - flatbuffers::ST_TABLE, 3, type_codes, type_refs, nullptr, names + flatbuffers::ST_TABLE, 4, type_codes, type_refs, nullptr, names }; return &tt; } diff --git a/source/core/Pipeline.cpp b/source/core/Pipeline.cpp index 7033108c3..2798239e5 100644 --- a/source/core/Pipeline.cpp +++ b/source/core/Pipeline.cpp @@ -41,7 +41,7 @@ static bool _supportQuant(const Op* op, const std::vector& inputs, cons case OpType_ConvInt8: case OpType_DepthwiseConvInt8: return true; - // case OpType_Eltwise: + // case OpType_Eltwise: case OpType_Raster: { for (auto input : inputs) { @@ -69,7 +69,7 @@ static bool _supportQuant(const Op* op, const std::vector& inputs, cons } else { return false; } - case OpType_BinaryOp: + case OpType_BinaryOp: return true; case OpType_Softmax: return true; @@ -80,7 +80,11 @@ static bool _supportQuant(const Op* op, const std::vector& inputs, cons case OpType_LayerNorm: return true; case OpType_UnaryOp: - return true; + if (op->main_as_UnaryOp()->tableInt8() || op->main_as_UnaryOp()->opType() == UnaryOpOperation_NEG || op->main_as_UnaryOp()->opType() == UnaryOpOperation_ABS || op->main_as_UnaryOp()->opType() == UnaryOpOperation_SIGN) { + return true; + } else { + return false; + } case OpType_PReLU: return true; default: diff --git a/source/core/Tensor.cpp b/source/core/Tensor.cpp index 4165f1ab7..28d5076a8 100644 --- a/source/core/Tensor.cpp +++ b/source/core/Tensor.cpp @@ -240,7 +240,7 @@ void Tensor::setType(int type) { mBuffer.type = halide_type_of(); break; default: - MNN_PRINT("Unsupported data type!"); + MNN_PRINT("Unsupported data type! %d\n", type); MNN_ASSERT(false); break; } diff --git a/test/MNNTestSuite.cpp b/test/MNNTestSuite.cpp index 157a54051..2b3aeb52a 100644 --- a/test/MNNTestSuite.cpp +++ b/test/MNNTestSuite.cpp @@ -56,6 +56,9 @@ int MNNTestSuite::run(const char* key, int precision, const char* flag) { } } } + for (auto& iter : runTimes) { + MNN_PRINT("%s cost time: %.3f ms\n", iter.first.c_str(), iter.second); + } if (wrongs.empty()) { MNN_PRINT("√√√ all <%s> tests passed.\n", key); } @@ -63,9 +66,6 @@ int MNNTestSuite::run(const char* key, int precision, const char* flag) { MNN_PRINT("Error: %s\n", wrong.c_str()); } printTestResult(wrongs.size(), runUnit - wrongs.size(), flag); - for (auto& iter : runTimes) { - MNN_PRINT("%s cost time: %.3f ms\n", iter.first.c_str(), iter.second); - } return wrongs.size(); } @@ -91,6 +91,9 @@ int MNNTestSuite::runAll(int precision, const char* flag) { wrongs.emplace_back(test->name); } } + for (auto& iter : runTimes) { + MNN_PRINT("%s cost time: %.3f ms\n", iter.first.c_str(), iter.second); + } if (wrongs.empty()) { MNN_PRINT("√√√ all tests passed.\n"); } @@ -98,8 +101,5 @@ int MNNTestSuite::runAll(int precision, const char* flag) { MNN_PRINT("Error: %s\n", wrong.c_str()); } printTestResult(wrongs.size(), suite->mTests.size() - wrongs.size(), flag); - for (auto& iter : runTimes) { - MNN_PRINT("%s cost time: %.3f ms\n", iter.first.c_str(), iter.second); - } return wrongs.size(); } diff --git a/test/core/BackendTest.cpp b/test/core/BackendTest.cpp index dd3381b9f..c40472ad2 100644 --- a/test/core/BackendTest.cpp +++ b/test/core/BackendTest.cpp @@ -572,7 +572,7 @@ bool nchwTonhwc(std::shared_ptr bn) { auto backendCopyData = hostTensorNHWC->host(); for (int i = 0; i < elementSize; ++i) { if (abs(backendCopyData[i] - temp[i]) >= F32_BF16_MAX_LOSS) { //Error of converting from float32 to bf16 is more than 0.001 - MNN_PRINT("Error for bn:%d, %f -> %f. F32_BF16_MAX_LOSS:%f\n", i, hostData[i], backendCopyData[i], F32_BF16_MAX_LOSS); + MNN_PRINT("Error for bn:%d, %f -> %f. F32_BF16_MAX_LOSS:%f\n", i, temp[i], backendCopyData[i], F32_BF16_MAX_LOSS); return false; } } diff --git a/tools/converter/source/onnx/IdentityOnnx.cpp b/tools/converter/source/onnx/IdentityOnnx.cpp index af2f7dbbd..d5dcb9dfe 100644 --- a/tools/converter/source/onnx/IdentityOnnx.cpp +++ b/tools/converter/source/onnx/IdentityOnnx.cpp @@ -24,3 +24,21 @@ void IdentityOnnx::run(MNN::OpT *dstOp, const onnx::NodeProto *onnxNode, } REGISTER_CONVERTER(IdentityOnnx, Identity); + + +DECLARE_OP_CONVERTER(DropoutOnnx); + +MNN::OpType DropoutOnnx::opType() { + return MNN::OpType_Dropout; +} +MNN::OpParameter DropoutOnnx::type() { + return MNN::OpParameter_NONE; +} + +void DropoutOnnx::run(MNN::OpT *dstOp, const onnx::NodeProto *onnxNode, + OnnxScope* scope) { + // Do nothing + return; +} + +REGISTER_CONVERTER(DropoutOnnx, Dropout); diff --git a/tools/converter/source/optimizer/merge/FuseFmhaV2.cpp b/tools/converter/source/optimizer/merge/FuseFmhaV2.cpp index 7c8ee3b85..fdd90a61b 100644 --- a/tools/converter/source/optimizer/merge/FuseFmhaV2.cpp +++ b/tools/converter/source/optimizer/merge/FuseFmhaV2.cpp @@ -247,6 +247,252 @@ FuseFmhaV2::FuseFmhaV2() { TemplateMerge::getInstance("Merge").insertTemplate("FuseFmhaV2", match, fold); } +class FuseSelfAttentionV2 { +public: + FuseSelfAttentionV2(); +private: + EXPRP node_q, node_k, node_v; + VARP var_q_weight, var_k_weight, var_v_weight; + VARP fmha_v2_input_; + int mNumHeads; +}; + +FuseSelfAttentionV2::FuseSelfAttentionV2() { + auto match = [this](EXPRP expr) -> bool { + auto config = Global::Get(); + if(!config->transformerFuse) { + return false; + } + // whether reshape + if (!expr->get() || !helpers::IsReshape(expr)) { + return false; + } + + EXPRP x, y, z; + + // whether transpose + x = expr->inputs().at(0)->expr().first; + if (!expr->get() || !helpers::IsTranspose(x)) { + return false; + } + z = x; + + // whether reshape + x = z->inputs().at(0)->expr().first; + if (!helpers::IsReshape(x)) { + return false; + } + z = x; + + // whether Einsum/MatMul + x = z->inputs().at(0)->expr().first; + if (helpers::IsMatMul(x)) { + z = x; + } else { + return false; + } + + // whether V + auto qk_pre = z->inputs().at(0)->expr().first; + auto v_pre = z->inputs().at(1)->expr().first; + z = GetFmhaV2BlockCommonNode(v_pre); + if (z == nullptr) { + return false; + } + mNumHeads = GetFmhaV2NumHeads(z); + if (mNumHeads == 0) { + return false; + } + node_v = z->inputs().at(0)->expr().first; + if (!helpers::IsMatMul(node_v)) { + return false; + } + + // whether cast + if (helpers::IsCast(qk_pre)) { + qk_pre = qk_pre->inputs().at(0)->expr().first; + } + z = qk_pre; + // whether softmax + if (!helpers::IsSoftmax(z)) { + return false; + } + + //whether add zero + x = z->inputs().at(0)->expr().first; + if (helpers::IsBinaryAdd(x)) { + z = x; + } else { + return false; + } + + //add two inputs + auto x_0 = z->inputs().at(0)->expr().first; + bool add_0_zero = false; + if (helpers::IsBinaryMul(x_0)) { + auto temp_0 = x_0->inputs().at(0)->expr().first; + auto temp_1 = x_0->inputs().at(1)->expr().first; + if (helpers::IsConstant(temp_0)) { + float mul_y = x_0->inputs().at(0)->readMap()[0]; + if(mul_y >= -0.0000001 && mul_y <= 0.0000001) { + add_0_zero = true; + } + } + if (helpers::IsConstant(temp_1)) { + float mul_y = x_0->inputs().at(1)->readMap()[0]; + if(mul_y >= -0.0000001 && mul_y <= 0.0000001) { + add_0_zero = true; + } + } + } else { + return false; + } + + auto x_1 = z->inputs().at(1)->expr().first; + bool add_1_zero = false; + if (helpers::IsBinaryMul(x_1)) { + auto temp_0 = x_1->inputs().at(0)->expr().first; + auto temp_1 = x_1->inputs().at(1)->expr().first; + if (helpers::IsConstant(temp_0)) { + float mul_y = x_1->inputs().at(0)->readMap()[0]; + if(mul_y >= -0.0000001 && mul_y <= 0.0000001) { + add_1_zero = true; + } + } + if (helpers::IsConstant(temp_1)) { + float mul_y = x_1->inputs().at(1)->readMap()[0]; + if(mul_y >= -0.0000001 && mul_y <= 0.0000001) { + add_1_zero = true; + } + } + } else { + return false; + } + + if(add_0_zero && !add_1_zero) { + x = z->inputs().at(1)->expr().first; + if(helpers::IsConstant(x->inputs().at(0)->expr().first)) { + x = x->inputs().at(1)->expr().first; + } else { + x = x->inputs().at(0)->expr().first; + } + } else if(!add_0_zero && add_1_zero) { + x = z->inputs().at(0)->expr().first; + if(helpers::IsConstant(x->inputs().at(0)->expr().first)) { + x = x->inputs().at(1)->expr().first; + } else { + x = x->inputs().at(0)->expr().first; + } + } else { + return false; + } + + //whether matmul + if (helpers::IsMatMul(x)) { + z = x; + } else { + return false; + } + + auto q_pre = z->inputs().at(0)->expr().first; + auto k_pre = z->inputs().at(1)->expr().first; + if(helpers::IsTranspose(k_pre)) { + k_pre = k_pre->inputs().at(0)->expr().first; + } + z = GetFmhaV2BlockCommonNode(k_pre); + if (z == nullptr) { + return false; + } + + if (mNumHeads != GetFmhaV2NumHeads(z)) { + return false; + } + node_k = z->inputs().at(0)->expr().first; + // whether mul(scale) + if (helpers::IsBinaryMul(node_k)) { + node_k = node_k->inputs().at(0)->expr().first; + } + + if (!helpers::IsMatMul(node_k)) { + return false; + } + + // whether slice + if (helpers::IsSlice(q_pre)) { + q_pre = q_pre->inputs().at(0)->expr().first; + } + z = GetFmhaV2BlockCommonNode(q_pre); + if (z == nullptr) { + return false; + } + if (mNumHeads != GetFmhaV2NumHeads(z)) { + return false; + } + node_q = z->inputs().at(0)->expr().first; + if (!helpers::IsMatMul(node_q)) { + return false; + } + + // QKV -> one source + if (node_q->inputs().at(0)->expr().first != node_k->inputs().at(0)->expr().first || node_q->inputs().at(0)->expr().first != node_v->inputs().at(0)->expr().first) { + return false; + } + fmha_v2_input_ = node_q->inputs().at(0); + var_q_weight = node_q->inputs().at(1); + var_k_weight = node_k->inputs().at(1); + var_v_weight = node_v->inputs().at(1); + + if(!helpers::IsConstant(var_q_weight->expr().first) || !helpers::IsConstant(var_k_weight->expr().first) || !helpers::IsConstant(var_v_weight->expr().first)) { + return false; + } + return true; + }; + + auto fold = [this](EXPRP expr) -> bool { + auto config = Global::Get(); + auto version = config->targetVersion; + if (version < 2.8f) { + // For target version < 2.8 , don't support fmha_v2 + return false; + } + + auto* var_q_weight_info = var_q_weight->getInfo(); + auto* var_k_weight_info = var_k_weight->getInfo(); + auto* var_v_weight_info = var_v_weight->getInfo(); + + if (!var_q_weight_info || !var_k_weight_info || !var_v_weight_info || var_q_weight_info->size != var_k_weight_info->size || var_q_weight_info->size != var_v_weight_info->size) { + return false; + } + int size = var_q_weight_info->size; + int C = var_q_weight_info->dim[0]; + int H = mNumHeads; + int D = var_q_weight_info->dim[1] / H; + if (var_q_weight_info->dim[1] % H != 0) { + return false; + } + + // FuseQKV_Weight + /* [C, H, D] -> [C, H, 3, D]*/ + auto output = _MatMul(fmha_v2_input_, _Reshape(_Concat({_Reshape(var_q_weight, {C, H, D}), _Reshape(var_k_weight, {C, H, D}), _Reshape(var_v_weight, {C, H, D})}, -1), {C, H*3*D}), false, false); + + std::unique_ptr param_fmha(new MNN::FmhaV2ParamT); + param_fmha->heads = mNumHeads; + + std::unique_ptr fmha_v2_op(new OpT); + fmha_v2_op->name = "FmhaV2_" + expr->name(); + fmha_v2_op->type = OpType_FmhaV2; + fmha_v2_op->main.type = OpParameter_FmhaV2Param; + fmha_v2_op->main.value = param_fmha.release(); + + auto fmha_v2_expr = Variable::create(Expr::create(fmha_v2_op.get(), { output }, 1)); + + fmha_v2_expr->setName(expr->name()); + Expr::replace(expr, fmha_v2_expr->expr().first); + return true /*modified*/; + }; + TemplateMerge::getInstance("Merge").insertTemplate("FuseSelfAttentionV2", match, fold); +} + class FuseSelfFmhaV2 { public: @@ -384,6 +630,7 @@ FuseSelfFmhaV2::FuseSelfFmhaV2() { static FuseFmhaV2 g_fuse_fmhaV2; static FuseSelfFmhaV2 g_fuse_self_fmhaV2; +static FuseSelfAttentionV2 g_fuse_self_attentionV2; } // namespace Express } // namespace MNN diff --git a/tools/converter/source/optimizer/merge/FuseGroupNorm.cpp b/tools/converter/source/optimizer/merge/FuseGroupNorm.cpp index 58d9378cb..77ff1cabf 100644 --- a/tools/converter/source/optimizer/merge/FuseGroupNorm.cpp +++ b/tools/converter/source/optimizer/merge/FuseGroupNorm.cpp @@ -30,6 +30,7 @@ class FuseGroupNormWithSwish { bool mHasPrefixAdd = false; VARP gamma_var_; VARP beta_var_; + EXPRP mGroupNorm; int mGroup; }; @@ -42,6 +43,9 @@ bool IsSigmoid(EXPRP expr) { if (op->type() == OpType_Sigmoid) { return true; } + if (op->type() == OpType_UnaryOp && op->main_as_UnaryOp()->opType() == UnaryOpOperation_SIGMOID) { + return true; + } return false; } bool IsLayerNorm(EXPRP expr) { @@ -54,12 +58,12 @@ bool IsLayerNorm(EXPRP expr) { } return false; } -bool IsGroupNorm(EXPRP expr) { +bool IsGroupNormNoSwish(EXPRP expr) { const Op* op = expr->get(); if (op == nullptr) { return false; } - if (op->type() == OpType_GroupNorm) { + if (op->type() == OpType_GroupNorm && op->main_as_GroupNorm()->bSwish() == 0) { return true; } return false; @@ -80,19 +84,16 @@ bool FuseGroupNormWithSwish::match_group_norm(EXPRP expr, bool testSwish) { // mul x = expr->inputs().at(0)->expr().first; y = expr->inputs().at(1)->expr().first; - if (helpers::IsBinaryAdd(x) && IsSigmoid(y) && (x == y->inputs().at(0)->expr().first)) { + if (IsGroupNormNoSwish(x) && IsSigmoid(y) && (x == y->inputs().at(0)->expr().first)) { z = x; - } else if (helpers::IsBinaryAdd(y) && IsSigmoid(x) && (y == x->inputs().at(0)->expr().first)) { + } else if (IsGroupNormNoSwish(y) && IsSigmoid(x) && (y == x->inputs().at(0)->expr().first)) { z = y; } else { return false; } mSwish = 1; - // cast - x = z->inputs().at(0)->expr().first; - if (helpers::IsCast(x)) { - z = x; - } + mGroupNorm = z; + return true; } else if (!testSwish && helpers::IsBinaryAdd(expr)) { z = expr; @@ -178,6 +179,31 @@ bool FuseGroupNormWithSwish::fold_group_norm(EXPRP expr, bool testSwish) { } std::unique_ptr group_norm(new MNN::GroupNormT); + + if(mSwish) { + auto gn = mGroupNorm->get()->main_as_GroupNorm(); + group_norm->epsilon = gn->epsilon(); + group_norm->bSwish = 1; + group_norm->group = gn->group(); + + int size = gn->gamma()->size(); + group_norm->gamma.resize(size); + group_norm->beta.resize(size); + memcpy(group_norm->gamma.data(), gn->gamma()->data(), size * sizeof(float)); + memcpy(group_norm->beta.data(), gn->beta()->data(), size * sizeof(float)); + + std::unique_ptr group_norm_op(new OpT); + group_norm_op->name = mGroupNorm->name(); + group_norm_op->type = OpType_GroupNorm; + group_norm_op->main.type = OpParameter_GroupNorm; + group_norm_op->main.value = group_norm.release(); + + auto group_norm_expr = Variable::create(Expr::create(group_norm_op.get(), mGroupNorm->inputs(), 1)); + group_norm_expr->setName("GroupNorm_" + expr->name()); + Expr::replace(expr, group_norm_expr->expr().first); + return true /*modified*/; + } + group_norm->epsilon = mEpsilon; group_norm->bSwish = mSwish; group_norm->group = mGroup; diff --git a/tools/converter/source/optimizer/merge/FuseSplitGeLu.cpp b/tools/converter/source/optimizer/merge/FuseSplitGeLu.cpp index c7a331c10..55ef9f0b5 100644 --- a/tools/converter/source/optimizer/merge/FuseSplitGeLu.cpp +++ b/tools/converter/source/optimizer/merge/FuseSplitGeLu.cpp @@ -52,8 +52,20 @@ FuseSplitGeLu::FuseSplitGeLu() { y = expr->inputs().at(1)->expr().first; if (helpers::IsBinaryMul(x) && helpers::IsSlice(y)) { z = x; + if(!helpers::IsConstant(y->inputs().at(1)->expr().first) || y->inputs().at(1)->readMap()[0] != 0) { + return false; + } + if(!helpers::IsConstant(y->inputs().at(3)->expr().first) || y->inputs().at(3)->readMap()[0] != -1) { + return false; + } } else if (helpers::IsBinaryMul(y) && helpers::IsSlice(x)) { z = y; + if(!helpers::IsConstant(x->inputs().at(1)->expr().first) || x->inputs().at(1)->readMap()[0] != 0) { + return false; + } + if(!helpers::IsConstant(x->inputs().at(3)->expr().first) || x->inputs().at(3)->readMap()[0] != -1) { + return false; + } } else { return false; } @@ -108,22 +120,35 @@ FuseSplitGeLu::FuseSplitGeLu() { } // slice x = z->inputs().at(0)->expr().first; - + auto res = z; mHasPrefixAdd = false; if (helpers::IsBinaryAdd(x)) { z = x; x = z->inputs().at(0)->expr().first; y = z->inputs().at(1)->expr().first; if (helpers::IsConstant(x)){ - split_gelu_input_0 = z->inputs().at(1); - split_gelu_input_1 = z->inputs().at(0); + if(z->inputs().at(0)->getInfo()->dim.size() == 1) { + split_gelu_input_0 = z->inputs().at(1); + split_gelu_input_1 = z->inputs().at(0); + } else { + split_gelu_input_0 = res->inputs().at(0); + return true; + } + } else if (helpers::IsConstant(y)){ + if(z->inputs().at(1)->getInfo()->dim.size() == 1) { + split_gelu_input_0 = z->inputs().at(0); + split_gelu_input_1 = z->inputs().at(1); + } else { + split_gelu_input_0 = res->inputs().at(0); + return true; + } } else { - split_gelu_input_0 = z->inputs().at(0); - split_gelu_input_1 = z->inputs().at(1); + split_gelu_input_0 = res->inputs().at(0); + return true; } mHasPrefixAdd = true; } else { - split_gelu_input_0 = z->inputs().at(0); + split_gelu_input_0 = res->inputs().at(0); } return true; }; diff --git a/tools/converter/source/optimizer/onnxextra/ResolveIdentityOnnx.cpp b/tools/converter/source/optimizer/onnxextra/ResolveIdentityOnnx.cpp deleted file mode 100644 index 3d202bcb1..000000000 --- a/tools/converter/source/optimizer/onnxextra/ResolveIdentityOnnx.cpp +++ /dev/null @@ -1,56 +0,0 @@ -// -// ResolveIdentityOnnx.cpp -// MNNConverter -// -// Created by MNN on 2019/10/24. -// Copyright © 2018, Alibaba Group Holding Limited -// - -#include "MNN_generated.h" -#include "OnnxExtraManager.hpp" - -namespace MNN { -namespace Express { - -class ResolveIdentityOnnx : public OnnxExtraManager::Transform { -public: - virtual EXPRP onExecute(EXPRP expr) const override { - auto inputs = expr->inputs(); - MNN_THROW_CHECK(inputs.size() == 1, "Identity Should have one input"); - - auto outputs = expr->outputs(); - MNN_THROW_CHECK(outputs.size() == 1, "Identity Should have one output"); - auto outputVaribale = outputs.front(); - - auto outputExpr = outputVaribale.lock(); - auto outputExprOp = outputExpr->get(); - - std::unique_ptr newOp(new OpT); - newOp->name = outputExprOp->name()->str(); - newOp->type = outputExprOp->type(); - newOp->main.type = outputExprOp->main_type(); - newOp->main.value = const_cast(outputExprOp->main()); - - auto outputExprInputs = outputExpr->inputs(); - - // find the matched input, then replace it - const int size = outputExprInputs.size(); - for (int i = 0; i < size; ++i) { - if (outputExprInputs[i]->expr().first.get() == outputExpr.get()) { - outputExprInputs[i] = inputs[0]; - break; - } - } - return Expr::create(newOp.get(), outputExprInputs); - } -}; - -static auto gRegister = []() { - OnnxExtraManager::get()->insert("Dropout", std::shared_ptr(new ResolveIdentityOnnx)); - - OnnxExtraManager::get()->insert("Identity", std::shared_ptr(new ResolveIdentityOnnx)); - return true; -}(); - -} // namespace Express -} // namespace MNN diff --git a/tools/converter/source/optimizer/postconvert/MergeBNToConvolution.cpp b/tools/converter/source/optimizer/postconvert/MergeBNToConvolution.cpp index 2cfbfd13c..73aaa04c3 100644 --- a/tools/converter/source/optimizer/postconvert/MergeBNToConvolution.cpp +++ b/tools/converter/source/optimizer/postconvert/MergeBNToConvolution.cpp @@ -53,13 +53,18 @@ class MergeBNToConvolution : public MergeToConvolution { if (convolutionOp->type == OpType_Deconvolution) { int inputCount = conv2D->weight.size() / outputCount / conv2D->common->kernelX / conv2D->common->kernelY; - for (int i = 0; i < inputCount; ++i) { - auto dstPos = i * outputCount * conv2D->common->kernelY * conv2D->common->kernelX; - for (int j = 0; j < outputCount; ++j) { - auto dstPosJ = dstPos + j * conv2D->common->kernelY * conv2D->common->kernelX; - float a = alpha[j]; - for (int k = 0; k < conv2D->common->kernelY * conv2D->common->kernelX; ++k) { - conv2D->weight[dstPosJ + k] *= a; + int suboutputCount = outputCount / convCommon->group; + for (int g=0; ggroup; ++g) { + auto alpg = alpha.data() + g * suboutputCount; + auto wOffset = conv2D->weight.size() / convCommon->group * g; + for (int i = 0; i < inputCount; ++i) { + auto dstPos = i * suboutputCount * conv2D->common->kernelY * conv2D->common->kernelX; + for (int j = 0; j < suboutputCount; ++j) { + auto dstPosJ = dstPos + j * conv2D->common->kernelY * conv2D->common->kernelX; + float a = alpg[j]; + for (int k = 0; k < conv2D->common->kernelY * conv2D->common->kernelX; ++k) { + conv2D->weight[dstPosJ + k + wOffset] *= a; + } } } } diff --git a/tools/converter/source/optimizer/postconvert/MergeScaleToConvolution.cpp b/tools/converter/source/optimizer/postconvert/MergeScaleToConvolution.cpp index 9b3d219cd..d1409ca01 100644 --- a/tools/converter/source/optimizer/postconvert/MergeScaleToConvolution.cpp +++ b/tools/converter/source/optimizer/postconvert/MergeScaleToConvolution.cpp @@ -6,6 +6,7 @@ // Copyright © 2018, Alibaba Group Holding Limited // +#include #include "../PostTreatUtils.hpp" #include "MergeToConvolution.hpp" @@ -41,13 +42,18 @@ class MergeScaleToConvolution : public MergeToConvolution { if (convolutionOp->type == OpType_Deconvolution) { int inputCount = conv2D->weight.size() / outputCount / conv2D->common->kernelX / conv2D->common->kernelY; - for (int i = 0; i < inputCount; ++i) { - auto dstPos = i * outputCount * conv2D->common->kernelY * conv2D->common->kernelX; - for (int j = 0; j < outputCount; ++j) { - auto dstPosJ = dstPos + j * conv2D->common->kernelY * conv2D->common->kernelX; - float a = alpha[j]; - for (int k = 0; k < conv2D->common->kernelY * conv2D->common->kernelX; ++k) { - conv2D->weight[dstPosJ + k] *= a; + int suboutputCount = outputCount / convCommon->group; + for (int g=0; ggroup; ++g) { + auto alpg = alpha.data() + g * suboutputCount; + auto wOffset = conv2D->weight.size() / convCommon->group * g; + for (int i = 0; i < inputCount; ++i) { + auto dstPos = i * suboutputCount * conv2D->common->kernelY * conv2D->common->kernelX; + for (int j = 0; j < suboutputCount; ++j) { + auto dstPosJ = dstPos + j * conv2D->common->kernelY * conv2D->common->kernelX; + float a = alpg[j]; + for (int k = 0; k < conv2D->common->kernelY * conv2D->common->kernelX; ++k) { + conv2D->weight[dstPosJ + k + wOffset] *= a; + } } } } diff --git a/tools/converter/source/optimizer/postconvert/MergeToConvolution.hpp b/tools/converter/source/optimizer/postconvert/MergeToConvolution.hpp index 80f1b1139..24bc2251a 100644 --- a/tools/converter/source/optimizer/postconvert/MergeToConvolution.hpp +++ b/tools/converter/source/optimizer/postconvert/MergeToConvolution.hpp @@ -6,6 +6,7 @@ // Copyright © 2018, Alibaba Group Holding Limited // +#include #include "../PostTreatUtils.hpp" using namespace MNN; @@ -18,6 +19,10 @@ class MergeToConvolution : public PostConverter { virtual bool onExecute(std::unique_ptr& net) const override { // Merge Layer std::vector readyToDelete; + std::set outputNames; + for (auto n : net->outputName) { + outputNames.insert(n); + } for (auto iter = net->oplists.begin(); iter != net->oplists.end(); iter++) { MNN::OpT& currentOp = *(iter->get()); if (currentOp.type != MNN::OpType_Convolution @@ -27,6 +32,9 @@ class MergeToConvolution : public PostConverter { continue; } DCHECK(currentOp.outputIndexes.size() == 1) << "Conv output ERROR!"; + if (outputNames.find(net->tensorName[currentOp.outputIndexes[0]]) != outputNames.end()) { + continue; + } // merge Batchnorm/Relu/Relu6 to Convolution std::vector nextOp = PostTreatUtils::_findOpByInputIndex(currentOp.outputIndexes[0], net.get()); diff --git a/tools/converter/source/optimizer/postconvert/TransformGroupConvolution.cpp b/tools/converter/source/optimizer/postconvert/TransformGroupConvolution.cpp index 0e42c5769..1c5498e26 100644 --- a/tools/converter/source/optimizer/postconvert/TransformGroupConvolution.cpp +++ b/tools/converter/source/optimizer/postconvert/TransformGroupConvolution.cpp @@ -6,6 +6,7 @@ // Copyright © 2018, Alibaba Group Holding Limited // +#include #include "../PostTreatUtils.hpp" using namespace MNN; class TransformGroupConvolution3D : public PostConverter { @@ -227,6 +228,9 @@ class TransformGroupConvolution : public PostConverter { int partBiasSize = conv2D->bias.size() / common->group; // Create Sub Convolution + flatbuffers::FlatBufferBuilder tmpBuilder; + tmpBuilder.Finish(Convolution2DCommon::Pack(tmpBuilder, common.get())); + auto originCommon = flatbuffers::GetRoot(tmpBuilder.GetBufferPointer()); for (int i = 0; i < common->group; ++i) { std::ostringstream opNameOs; auto newConvOp = new MNN::OpT; @@ -239,23 +243,10 @@ class TransformGroupConvolution : public PostConverter { auto newConvolutionT = new MNN::Convolution2DT; newConvOp->main.value = newConvolutionT; - newConvolutionT->common = std::unique_ptr(new MNN::Convolution2DCommonT); - newConvolutionT->common->kernelX = common->kernelX; - newConvolutionT->common->kernelY = common->kernelY; - newConvolutionT->common->dilateY = common->dilateY; - newConvolutionT->common->dilateX = common->dilateX; - newConvolutionT->common->strideX = common->strideX; - newConvolutionT->common->strideY = common->strideY; + newConvolutionT->common = std::unique_ptr(originCommon->UnPack()); newConvolutionT->common->group = 1; - newConvolutionT->common->padMode = common->padMode; newConvolutionT->common->outputCount = common->outputCount / common->group; newConvolutionT->common->inputCount = common->inputCount / common->group; - newConvolutionT->common->padX = common->padX; - newConvolutionT->common->padY = common->padY; - newConvolutionT->common->relu = common->relu; - newConvolutionT->common->relu6 = common->relu6; - newConvolutionT->common->outPads = common->outPads; - int startWeight = partWeightSize * i; int startBias = partBiasSize * i; for (int v = 0; v < partWeightSize; ++v) { diff --git a/tools/cpp/ExprDebug.hpp b/tools/cpp/ExprDebug.hpp index ce342a0dd..2b5688d58 100644 --- a/tools/cpp/ExprDebug.hpp +++ b/tools/cpp/ExprDebug.hpp @@ -242,7 +242,7 @@ static void _initTensorStatic() { continue; } auto data = res.second; - MNN_PRINT("%s [Input] %s_%d, Max: %f, Min: %f, Avg: %f, [", info->type().c_str(), opName.c_str(), i, std::get<0>(data), std::get<1>(data), std::get<2>(data)); + MNN_PRINT("%s [Input] %s_%d, type:%d-%d, Max: %f, Min: %f, Avg: %f, [", info->type().c_str(), opName.c_str(), i, ntensor->getType().code, ntensor->getType().bits, std::get<0>(data), std::get<1>(data), std::get<2>(data)); for (int v=0; vdimensions(); ++v) { MNN_PRINT("%d", ntensor->length(v)); if (v!=ntensor->dimensions()-1) { @@ -265,7 +265,7 @@ static void _initTensorStatic() { continue; } auto data = res.second; - MNN_PRINT("%s [Output] %s_%d, Max: %f, Min: %f, Avg: %f, [", info->type().c_str(), opName.c_str(), i, std::get<0>(data), std::get<1>(data), std::get<2>(data)); + MNN_PRINT("%s [Output] %s_%d, type:%d-%d, Max: %f, Min: %f, Avg: %f, [", info->type().c_str(), opName.c_str(), i, ntensor->getType().code, ntensor->getType().bits, std::get<0>(data), std::get<1>(data), std::get<2>(data)); for (int v=0; vdimensions(); ++v) { MNN_PRINT("%d", ntensor->length(v)); if (v!=ntensor->dimensions()-1) { diff --git a/tools/cpp/testModel.cpp b/tools/cpp/testModel.cpp index 6f7d819f4..30d2d5c2c 100644 --- a/tools/cpp/testModel.cpp +++ b/tools/cpp/testModel.cpp @@ -79,6 +79,7 @@ int main(int argc, const char* argv[]) { if (argc > 6) { precision = (MNN::BackendConfig::PrecisionMode)stringConvert(argv[6]); } + std::shared_ptr net = std::shared_ptr(MNN::Interpreter::createFromFile(modelPath), [](void* net) { MNN::Interpreter::destroy((MNN::Interpreter*)net); diff --git a/tools/cv/source/imgcodecs/imgcodecs.cpp b/tools/cv/source/imgcodecs/imgcodecs.cpp index 04d577dcb..83a83ecd5 100644 --- a/tools/cv/source/imgcodecs/imgcodecs.cpp +++ b/tools/cv/source/imgcodecs/imgcodecs.cpp @@ -18,7 +18,7 @@ #define STBI_ONLY_PNG #define STBI_ONLY_BMP #define STB_IMAGE_STATIC - +#define STB_IMAGE_WRITE_STATIC #include "stb_image.h" #define STB_IMAGE_WRITE_IMPLEMENTATION #include "stb_image_write.h" diff --git a/tools/quantization/Helper.cpp b/tools/quantization/Helper.cpp index 487ebb9b9..9bbd29934 100644 --- a/tools/quantization/Helper.cpp +++ b/tools/quantization/Helper.cpp @@ -59,7 +59,7 @@ void Helper::readClibrationFiles(std::vector& images, const std::st continue; } const std::string fileName = filePath + "\\" + ffd.cFileName; - if (INVALID_FILE_ATTRIBUTES != GetFileAttributes(fileName.c_str()) && GetLastError() != ERROR_FILE_NOT_FOUND) { + if (INVALID_FILE_ATTRIBUTES != GetFileAttributes(fileName.c_str()) && FILE_ATTRIBUTE_DIRECTORY) { if (*usedImageNum == 0) { // use all images in the folder images.push_back(fileName); @@ -73,6 +73,22 @@ void Helper::readClibrationFiles(std::vector& images, const std::st else { break; } + } else { + if (INVALID_FILE_ATTRIBUTES != GetFileAttributes(fileName.c_str()) && GetLastError() != ERROR_FILE_NOT_FOUND) { + if (*usedImageNum == 0) { + // use all images in the folder + images.push_back(fileName); + count++; + } + else if (count < *usedImageNum) { + // use usedImageNum images + images.push_back(fileName); + count++; + } + else { + break; + } + } } } @@ -83,13 +99,13 @@ void Helper::readClibrationFiles(std::vector& images, const std::st MNN_ERROR("open %s failed!\n", filePath.c_str()); return; } + struct stat s; struct dirent* ent = readdir(root); while (ent != NULL) { if (ent->d_name[0] != '.') { - const std::string fileName = filePath + "/" + ent->d_name; - if (fileExist(fileName)) { - // std::cout << "==> " << fileName << std::endl; - // DLOG(INFO) << fileName; + const std::string fileName = filePath + ent->d_name; + stat(fileName.c_str(), &s); + if (s.st_mode & S_IFDIR) { if (*usedImageNum == 0) { // use all images in the folder images.push_back(fileName); @@ -101,6 +117,22 @@ void Helper::readClibrationFiles(std::vector& images, const std::st } else { break; } + } else { + if (fileExist(fileName)) { + // std::cout << "==> " << fileName << std::endl; + // DLOG(INFO) << fileName; + if (*usedImageNum == 0) { + // use all images in the folder + images.push_back(fileName); + count++; + } else if (count < *usedImageNum) { + // use usedImageNum images + images.push_back(fileName); + count++; + } else { + break; + } + } } } ent = readdir(root); @@ -108,11 +140,10 @@ void Helper::readClibrationFiles(std::vector& images, const std::st #endif *usedImageNum = images.size(); - DLOG(INFO) << "used image num: " << images.size(); + DLOG(INFO) << "used dataset num: " << images.size(); } -void Helper::preprocessInput(MNN::CV::ImageProcess* pretreat, PreprocessConfig preprocessConfig, - const std::string& filename, MNN::Tensor* input, InputType inputType) { +void Helper::preprocessInput(MNN::CV::ImageProcess* pretreat, PreprocessConfig preprocessConfig, const std::string& filename, MNN::Tensor* input, InputType inputType) { if (inputType == InputType::IMAGE) { int originalWidth, originalHeight, comp; auto bitmap32bits = stbi_load(filename.c_str(), &originalWidth, &originalHeight, &comp, 4); diff --git a/tools/quantization/TensorStatistic.cpp b/tools/quantization/TensorStatistic.cpp index 734fa1a92..fad617d31 100644 --- a/tools/quantization/TensorStatistic.cpp +++ b/tools/quantization/TensorStatistic.cpp @@ -12,6 +12,7 @@ #include #include #include "logkit.h" +#include "core/TensorUtils.hpp" // Given distribution P and Q, KL-Divergence is // Sum(P[i] * log(P[i] / Q[i])) @@ -53,30 +54,21 @@ void TensorStatistic::updateRange() { return; } mUpdatedRangeFlags = true; - mOriginTensor->copyToHostTensor(mHostTensor.get()); - int batch = mHostTensor->batch(); - int channel = mHostTensor->channel(); - int width = mHostTensor->width(); - int height = mHostTensor->height(); - auto area = width * height; - if (area == 0) { - area = 1; + auto tmpTensor = mOriginTensor; + bool res = mOriginTensor->copyToHostTensor(mHostTensor.get()); + if (res) { + tmpTensor = mHostTensor.get(); } - - for (int n = 0; n < batch; ++n) { - auto dataBatch = mHostTensor->host() + n * mHostTensor->stride(0); - for (int c = 0; c < channel; ++c) { - auto minValue = mRange.first; - auto maxValue = mRange.second; - auto dataChannel = dataBatch + c * mHostTensor->stride(1); - for (int v = 0; v < area; ++v) { - minValue = std::min(minValue, dataChannel[v]); - maxValue = std::max(maxValue, dataChannel[v]); - } - mRange.first = minValue; - mRange.second = maxValue; - } + int size = tmpTensor->elementSize(); + float* dataPtr = tmpTensor->host(); + auto minValue = mRange.first; + auto maxValue = mRange.second; + for (int i = 0; i < size; ++i) { + minValue = std::min(minValue, dataPtr[i]); + maxValue = std::max(maxValue, dataPtr[i]); } + mRange.first = minValue; + mRange.second = maxValue; // if (mRange.first > 0.0f) { // mRange.first = 0.0f; // } @@ -102,36 +94,22 @@ void TensorStatistic::updateDistribution() { return; } mUpdatedDistributionFlag = true; - mOriginTensor->copyToHostTensor(mHostTensor.get()); - int batch = mHostTensor->batch(); - int channel = mHostTensor->channel(); - int width = mHostTensor->width(); - int height = mHostTensor->height(); - auto area = width * height; - if (area == 0) { - area = 1; + auto tmpTensor = mOriginTensor; + bool res = mOriginTensor->copyToHostTensor(mHostTensor.get()); + if (res) { + tmpTensor = mHostTensor.get(); } // float midValue = (mRange.second + mRange.first) / 2.0f; float midValue = 0.f; - for (int n = 0; n < batch; ++n) { - auto dataBatch = mHostTensor->host() + n * mHostTensor->stride(0); - for (int c = 0; c < channel; ++c) { - if (!mValid) { - continue; - } - auto multi = mInterval; - auto target = mDistribution.data(); - auto dataChannel = dataBatch + c * mHostTensor->stride(1); - for (int v = 0; v < area; ++v) { - auto data = dataChannel[v] - midValue; - if (data == 0) { - continue; - } - int index = static_cast(fabs(data) * multi); - index = std::min(index, mBinNumber - 1); - target[index] += 1.0f; - } + auto ptr = tmpTensor->host(); + for (int i = 0; i < tmpTensor->elementSize(); ++i) { + auto data = ptr[i] - midValue; + if (abs(data) <= 1e-6) { + continue; } + int index = static_cast(fabs(data) * mInterval); + index = std::min(index, mBinNumber - 1); + mDistribution[index] += 1.0f; } } diff --git a/tools/quantization/calibration.cpp b/tools/quantization/calibration.cpp index 32d13aaad..4ae33f3d8 100644 --- a/tools/quantization/calibration.cpp +++ b/tools/quantization/calibration.cpp @@ -39,12 +39,159 @@ #include "core/ConvolutionCommon.hpp" #include + +#include +#include +#define DUMP_NUM_DATA(type) \ + auto data = tensor->host(); \ + for (int z = 0; z < outside; ++z) { \ + for (int x = 0; x < width; ++x) { \ + outputOs << data[x + z * width] << "\t"; \ + } \ + outputOs << "\n"; \ + } + +#define DUMP_CHAR_DATA(type) \ + auto data = tensor->host(); \ + for (int z = 0; z < outside; ++z) { \ + for (int x = 0; x < width; ++x) { \ + outputOs << static_cast(data[x + z * width]) << "\t"; \ + } \ + outputOs << "\n"; \ + } + +static void dumpTensor2File(const Tensor* tensor, const char* file) { + std::ofstream outputOs(file); + auto type = tensor->getType(); + + int dimension = tensor->buffer().dimensions; + int width = 1; + if (dimension > 1) { + width = tensor->length(dimension - 1); + } + + const int outside = tensor->elementSize() / width; + + const auto dataType = type.code; + const auto dataBytes = type.bytes(); + + if (dataType == halide_type_float) { + DUMP_NUM_DATA(float); + } + if (dataType == halide_type_int && dataBytes == 4) { + DUMP_NUM_DATA(int32_t); + } + if (dataType == halide_type_uint && dataBytes == 1) { + DUMP_CHAR_DATA(uint8_t); + } + if (dataType == halide_type_int && dataBytes == 1) { +#ifdef MNN_USE_SSE + auto data = tensor->host(); + for (int z = 0; z < outside; ++z) { + for (int x = 0; x < width; ++x) { + outputOs << (static_cast(data[x + z * width]) - 128) << "\t"; + } + outputOs << "\n"; + } +#else + DUMP_CHAR_DATA(int8_t); +#endif + } +} + using namespace MNN::CV; using namespace MNN::Train; using namespace MNN::Express; -Calibration::Calibration(MNN::NetT* model, const uint8_t* modelBuffer, const int bufferSize, const std::string& configPath, std::string originalModelFile, std::string destModelFile) - : _originalModel(model), _originalModelFile(originalModelFile), _destModelFile(destModelFile) { +static std::vector getModuleInputs(std::string file, const Module::Info* netInfo, std::vector inputNames, std::map> inputShape) { +#define LOAD_DATA(TYPE)\ +std::ostringstream fileNameOs;\ +fileNameOs << file << "/" << inputName << ".txt";\ +auto fileName = fileNameOs.str();\ +std::ifstream inputOs(fileName.c_str());\ +if (inputOs.fail()) {\ +MNN_ERROR("TESTERROR Can't open %s\n", fileName.c_str());\ +continue;\ +}\ +for (int i=0; isize; ++i) {\ +double tempValue;\ +inputOs >> tempValue;\ +ptr[i] = tempValue;\ +}\ + +#define LOAD_DATA_SHAPE() \ +std::ostringstream file_name_os;\ +file_name_os << file << "/input.json";\ +auto file_name = file_name_os.str();\ +std::ifstream input_os(file_name.c_str());\ +if (input_os.fail()) {\ +MNN_PRINT("input.json does not exit in %s, use default shape.\n", file.c_str());\ +dyInputShape=inputShape;\ +} else {\ +rapidjson::Document document;\ +std::ostringstream json_os;\ +json_os << input_os.rdbuf();\ +document.Parse(json_os.str().c_str());\ +if (document.HasParseError()) {\ +MNN_ERROR("Invalid json: %s\n", file_name.c_str());\ +}\ +auto cfgObj = document.GetObject();\ +if (cfgObj.HasMember("inputs")) {\ +auto inputsInfo = document["inputs"].GetArray();\ +for (auto iter = inputsInfo.begin(); iter !=inputsInfo.end(); iter++) {\ +auto obj = iter->GetObject();\ +std::string name = obj["name"].GetString();\ +if (obj.HasMember("shape")) {\ +auto dims = obj["shape"].GetArray();\ +std::vector shapes;\ +for (auto iter = dims.begin(); iter != dims.end(); iter++) {\ + shapes.emplace_back(iter->GetInt());\ +}\ +dyInputShape.insert(std::make_pair(name, shapes));\ +}\ +}\ +}\ +else {\ +MNN_ERROR("input.json must have inputs infomation!\n");\ +}\ +}\ + + std::vector inputs; + inputs.resize(netInfo->inputs.size()); + for (int i=0; iinputs[i].dim, netInfo->inputs[i].order, netInfo->inputs[i].type); + } + // Load inputs + std::map> dyInputShape; + LOAD_DATA_SHAPE() + for (int i=0; isecond; + inputs[i] = _Input(s, netInfo->defaultFormat, netInfo->inputs[i].type); + } + auto info = inputs[i]->getInfo(); + if (info->type == halide_type_of()){ + auto ptr = inputs[i]->writeMap(); + LOAD_DATA(float) + } else { + auto floatVar = _Input(info->dim, info->order, halide_type_of()); + auto ptr = floatVar->writeMap(); + LOAD_DATA(float) + auto temp = _Cast(floatVar, info->type); + inputs[i]->input(temp); + } + inputs[i] = _Convert(inputs[i], netInfo->inputs[i].order); + } + +#undef LOAD_DATA +#undef LOAD_DATA_SHAPE + return inputs; +} + +Calibration::Calibration(MNN::NetT* model, const uint8_t* modelBuffer, const int bufferSize, const std::string& configPath, std::string originalModelFile, std::string destModelFile) : _originalModel(model), _originalModelFile(originalModelFile), _destModelFile(destModelFile) { // when the format of input image is RGB/BGR, channels equal to 3, GRAY is 1 _channels = 3; @@ -92,124 +239,182 @@ Calibration::Calibration(MNN::NetT* model, const uint8_t* modelBuffer, const int _imageProcessConfig.sourceFormat = RGBA; _calibrationFileNum = 0; - { - if (picObj.HasMember("mean")) { - auto mean = picObj["mean"].GetArray(); - int cur = 0; - for (auto iter = mean.begin(); iter != mean.end(); iter++) { - _imageProcessConfig.mean[cur++] = iter->GetFloat(); - } - } - if (picObj.HasMember("normal")) { - auto normal = picObj["normal"].GetArray(); - int cur = 0; - for (auto iter = normal.begin(); iter != normal.end(); iter++) { - _imageProcessConfig.normal[cur++] = iter->GetFloat(); - } - } - if (picObj.HasMember("center_crop_h")) { - _preprocessConfig.centerCropHeight = picObj["center_crop_h"].GetFloat(); - } - if (picObj.HasMember("center_crop_w")) { - _preprocessConfig.centerCropWidth = picObj["center_crop_w"].GetFloat(); + + if (picObj.HasMember("mean")) { + auto mean = picObj["mean"].GetArray(); + int cur = 0; + for (auto iter = mean.begin(); iter != mean.end(); iter++) { + _imageProcessConfig.mean[cur++] = iter->GetFloat(); } - if (picObj.HasMember("width")) { - _width = picObj["width"].GetInt(); - _preprocessConfig.targetWidth = _width; - } - if (picObj.HasMember("height")) { - _height = picObj["height"].GetInt(); - _preprocessConfig.targetHeight = _height; + } + if (picObj.HasMember("normal")) { + auto normal = picObj["normal"].GetArray(); + int cur = 0; + for (auto iter = normal.begin(); iter != normal.end(); iter++) { + _imageProcessConfig.normal[cur++] = iter->GetFloat(); } - if (picObj.HasMember("batch_size")) { - _batch = picObj["batch_size"].GetInt(); + } + if (picObj.HasMember("center_crop_h")) { + _preprocessConfig.centerCropHeight = picObj["center_crop_h"].GetFloat(); + } + if (picObj.HasMember("center_crop_w")) { + _preprocessConfig.centerCropWidth = picObj["center_crop_w"].GetFloat(); + } + if (picObj.HasMember("width")) { + _width = picObj["width"].GetInt(); + _preprocessConfig.targetWidth = _width; + } + if (picObj.HasMember("height")) { + _height = picObj["height"].GetInt(); + _preprocessConfig.targetHeight = _height; + } + if (picObj.HasMember("batch_size")) { + _batch = picObj["batch_size"].GetInt(); + } + if (picObj.HasMember("quant_bits")) { + _quant_bits = picObj["quant_bits"].GetInt(); + } + if (!picObj.HasMember("path")) { + MNN_ERROR("calibration data path not set in .json config file\n"); + return; + } + _calibrationFilePath = picObj["path"].GetString(); + if (picObj.HasMember("used_image_num")) { + _calibrationFileNum = picObj["used_image_num"].GetInt(); + } + if (picObj.HasMember("used_sample_num")) { + _calibrationFileNum = picObj["used_sample_num"].GetInt(); + } + if (picObj.HasMember("feature_quantize_method")) { + std::string method = picObj["feature_quantize_method"].GetString(); + if (Helper::featureQuantizeMethod.find(method) != Helper::featureQuantizeMethod.end()) { + _featureQuantizeMethod = method; + } else { + MNN_ERROR("not supported feature quantization method: %s\n", method.c_str()); + return; } - if (picObj.HasMember("quant_bits")) { - _quant_bits = picObj["quant_bits"].GetInt(); + } + if (picObj.HasMember("weight_quantize_method")) { + std::string method = picObj["weight_quantize_method"].GetString(); + if (Helper::weightQuantizeMethod.find(method) != Helper::weightQuantizeMethod.end()) { + _weightQuantizeMethod = method; + } else { + MNN_ERROR("not supported weight quantization method: %s\n", method.c_str()); + return; } - if (!picObj.HasMember("path")) { - MNN_ERROR("calibration data path not set in .json config file\n"); + } + DLOG(INFO) << "Use feature quantization method: " << _featureQuantizeMethod; + DLOG(INFO) << "Use weight quantization method: " << _weightQuantizeMethod; + if (picObj.HasMember("feature_clamp_value")) { + float value = (int)picObj["feature_clamp_value"].GetFloat(); + if (value < 0.0f || value > 127.0f) { + MNN_ERROR("feature_clamp_value should be in (0, 127], got: %f\n", value); return; } - _calibrationFilePath = picObj["path"].GetString(); - if (picObj.HasMember("used_image_num")) { - _calibrationFileNum = picObj["used_image_num"].GetInt(); + _featureClampValue = value; + } + if (picObj.HasMember("weight_clamp_value")) { + float value = (int)picObj["weight_clamp_value"].GetFloat(); + if (value < 0.0f || value > 127.0f) { + MNN_ERROR("weight_clamp_value should be in (0, 127], got: %f\n", value); + return; } - if (picObj.HasMember("used_sample_num")) { - _calibrationFileNum = picObj["used_sample_num"].GetInt(); + _weightClampValue = value; + if (_quant_bits < 8) { + _weightClampValue = (float)(1 << (_quant_bits - 1)) - 1.0f; } - if (picObj.HasMember("feature_quantize_method")) { - std::string method = picObj["feature_quantize_method"].GetString(); - if (Helper::featureQuantizeMethod.find(method) != Helper::featureQuantizeMethod.end()) { - _featureQuantizeMethod = method; - } else { - MNN_ERROR("not supported feature quantization method: %s\n", method.c_str()); - return; - } + } + DLOG(INFO) << "feature_clamp_value: " << _featureClampValue; + DLOG(INFO) << "weight_clamp_value: " << _weightClampValue; + if (picObj.HasMember("winogradOpt") && picObj["winogradOpt"].GetBool() == true) { + if (_featureQuantizeMethod == "EMA") { + _winogradOpt = true; + } else { + DLOG(ERROR) << "winogradOpt only be available under EMA"; } - if (picObj.HasMember("weight_quantize_method")) { - std::string method = picObj["weight_quantize_method"].GetString(); - if (Helper::weightQuantizeMethod.find(method) != Helper::weightQuantizeMethod.end()) { - _weightQuantizeMethod = method; - } else { - MNN_ERROR("not supported weight quantization method: %s\n", method.c_str()); - return; - } + } + if (picObj.HasMember("skip_quant_op_names")) { + auto skip_quant_op_names = picObj["skip_quant_op_names"].GetArray(); + for (auto iter = skip_quant_op_names.begin(); iter != skip_quant_op_names.end(); iter++) { + std::string skip_quant_op_name = iter->GetString(); + _skip_quant_ops.emplace_back(skip_quant_op_name); + DLOG(INFO) << "skip quant op name: " << skip_quant_op_name; } - DLOG(INFO) << "Use feature quantization method: " << _featureQuantizeMethod; - DLOG(INFO) << "Use weight quantization method: " << _weightQuantizeMethod; - if (picObj.HasMember("feature_clamp_value")) { - float value = (int)picObj["feature_clamp_value"].GetFloat(); - if (value < 0.0f || value > 127.0f) { - MNN_ERROR("feature_clamp_value should be in (0, 127], got: %f\n", value); - return; - } - _featureClampValue = value; + } + if (picObj.HasMember("debug")) { + _debug = picObj["debug"].GetBool(); + } + _inputType = Helper::InputType::IMAGE; + if (picObj.HasMember("input_type")) { + std::string type = picObj["input_type"].GetString(); + if (type == "sequence") { + _inputType = Helper::InputType::SEQUENCE; } - if (picObj.HasMember("weight_clamp_value")) { - float value = (int)picObj["weight_clamp_value"].GetFloat(); - if (value < 0.0f || value > 127.0f) { - MNN_ERROR("weight_clamp_value should be in (0, 127], got: %f\n", value); - return; + } + + _module.reset(Module::load({}, {}, originalModelFile.c_str())); + auto moduleInfo = _module->getInfo(); + for (int i = 0; i < moduleInfo->inputNames.size(); ++i) { + mInputNames.emplace_back(moduleInfo->inputNames[i]); + } + for (int i = 0; i < moduleInfo->outputNames.size(); ++i) { + mOutputNames.emplace_back(moduleInfo->outputNames[i]); + } + bool checkOutput = false; + if (picObj.HasMember("inputs")) { + auto inputsInfo = document["inputs"].GetArray(); + for (auto iter = inputsInfo.begin(); iter !=inputsInfo.end(); iter++) { + auto obj = iter->GetObject(); + std::string name = obj["name"].GetString(); + MNN_PRINT("input: %s\n", name.c_str()); + if (obj.HasMember("value")) { + float value = obj["value"].GetFloat(); + mInputInfo.insert(std::make_pair(name, value)); } - _weightClampValue = value; - if (_quant_bits < 8) { - _weightClampValue = (float)(1 << (_quant_bits - 1)) - 1.0f; + if (obj.HasMember("shape")) { + auto dims = obj["shape"].GetArray(); + std::vector shapes; + for (auto iter = dims.begin(); iter != dims.end(); iter++) { + shapes.emplace_back(iter->GetInt()); + } + mInputShape.insert(std::make_pair(name, shapes)); } } - DLOG(INFO) << "feature_clamp_value: " << _featureClampValue; - DLOG(INFO) << "weight_clamp_value: " << _weightClampValue; - if (picObj.HasMember("winogradOpt") && picObj["winogradOpt"].GetBool() == true) { - if (_featureQuantizeMethod == "EMA") { - _winogradOpt = true; - } else { - DLOG(ERROR) << "winogradOpt only be available under EMA"; + } + if (!picObj.HasMember("inputs")) { // User do not provide input names and shapes. + if (mInputNames.size() > 1) { + MNN_ERROR("Error: Input names and shapes should provided in json file!\n"); + } + std::string name = mInputNames[0]; + auto shape = moduleInfo->inputs[0].dim; + auto dimensionFormat = moduleInfo->inputs[0].order; + if (dimensionFormat == NCHW || dimensionFormat == NC4HW4) { + if (shape.size() > 2) { + shape[2] = _preprocessConfig.targetHeight; } - } - if (picObj.HasMember("skip_quant_op_names")) { - auto skip_quant_op_names = picObj["skip_quant_op_names"].GetArray(); - for (auto iter = skip_quant_op_names.begin(); iter != skip_quant_op_names.end(); iter++) { - std::string skip_quant_op_name = iter->GetString(); - _skip_quant_ops.emplace_back(skip_quant_op_name); - DLOG(INFO) << "skip quant op name: " << skip_quant_op_name; + if (shape.size() > 3) { + shape[3] = _preprocessConfig.targetWidth; } - } - if (picObj.HasMember("debug")) { - _debug = picObj["debug"].GetBool(); - } - _inputType = Helper::InputType::IMAGE; - if (picObj.HasMember("input_type")) { - std::string type = picObj["input_type"].GetString(); - if (type == "sequence") { - _inputType = Helper::InputType::SEQUENCE; + } else { // NHWC + if (shape.size() > 1) { + shape[1] = _preprocessConfig.targetHeight; + } + if (shape.size() > 2) { + shape[2] = _preprocessConfig.targetWidth; } } + mInputShape.insert(std::make_pair(name, shape)); } + std::shared_ptr process(ImageProcess::create(_imageProcessConfig), ImageProcess::destroy); _process = process; // read images file names + if (_calibrationFilePath.back() != '/') { + _calibrationFilePath = _calibrationFilePath + "/"; + } Helper::readClibrationFiles(_calibrationFiles, _calibrationFilePath.c_str(), &_calibrationFileNum); + std::sort(_calibrationFiles.begin(), _calibrationFiles.end()); for (auto& op : _originalModel->oplists) { if (op->type == MNN::OpType_BatchNorm) { @@ -227,124 +432,46 @@ Calibration::Calibration(MNN::NetT* model, const uint8_t* modelBuffer, const int } } } - + + MNN::ScheduleConfig config; + config.backupType = MNN_FORWARD_CPU; + config.numThread = 1; + std::shared_ptr rtmgr(Executor::RuntimeManager::createRuntimeManager(config)); if (_featureQuantizeMethod == "KL" || _featureQuantizeMethod == "ADMM") { - _initMNNSession(modelBuffer, bufferSize); - _initMaps(); + rtmgr->setMode(Interpreter::Session_Debug); } -} - -std::vector Calibration::_getInputShape(std::string filename) { - std::vector inputShape; - if (_inputType == Helper::InputType::IMAGE) { - inputShape.resize(4); - auto inputTensorDataFormat = MNN::TensorUtils::getDescribe(_inputTensor)->dimensionFormat; - if (inputTensorDataFormat == MNN::MNN_DATA_FORMAT_NHWC) { - inputShape[0] = 1; - inputShape[1] = _height; - inputShape[2] = _width; - inputShape[3] = _channels; - } else { - inputShape[0] = 1; - inputShape[1] = _channels; - inputShape[2] = _height; - inputShape[3] = _width; - } + _module.reset(Module::load(mInputNames, mOutputNames, originalModelFile.c_str(), rtmgr)); // rtmgr.mode->debug + if (_debug) { + _moduleOrigin.reset(Module::load(mInputNames, mOutputNames, originalModelFile.c_str(), rtmgr)); // rtmgr.mode->debug } - if (_inputType == Helper::InputType::SEQUENCE) { - if (!Helper::stringEndWith(filename, ".txt")) { - MNN_ERROR("Error: only '.txt' files are supported for sequence input.\n"); - } - std::ifstream f(filename); - if (!f.is_open()) { - MNN_ERROR("open file %s failed.\n", filename.c_str()); - } - - std::string line; - _channels = 0; - while (std::getline(f, line)) { - std::stringstream ss(line); - float v; - int count = 0; - while (ss >> v) { - count++; - } - if (count > 0) { - _channels++; - _height = count; + if (_featureQuantizeMethod == "KL" || _featureQuantizeMethod == "ADMM") { + _initMNNSession(modelBuffer, bufferSize); + auto netInfo = _module->getInfo(); + if (_inputType == Helper::SEQUENCE) { + mInputs = getModuleInputs(_calibrationFiles[0], _module->getInfo(), mInputNames, mInputShape); + for (int i = 0; i < mInputs.size(); ++i) { + auto input = mInputs[i]; + auto name = mInputNames[i]; + std::string fileName = _calibrationFiles[0] + "/" + name + ".txt"; + auto inputTensor = (MNN::Tensor*)input->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, fileName, inputTensor, _inputType); } - } - - if (_channels == 0) { - MNN_ERROR("Error: no data found in file %s.", filename.c_str()); - } - - inputShape.resize(3); - auto inputTensorDataFormat = MNN::TensorUtils::getDescribe(_inputTensor)->dimensionFormat; - if (inputTensorDataFormat == MNN::MNN_DATA_FORMAT_NHWC) { - inputShape[0] = 1; - inputShape[1] = _height; - inputShape[2] = _channels; } else { - inputShape[0] = 1; - inputShape[1] = _channels; - inputShape[2] = _height; + mInputs.resize(1); + mInputs[0] = _Input(netInfo->inputs[0].dim, netInfo->inputs[0].order, netInfo->inputs[0].type); + auto inputTensor = (MNN::Tensor*)mInputs[0]->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, _calibrationFiles[0], inputTensor, _inputType); + // auto dest = mInputs[0]->writeMap(); + // Helper::preprocessInput((float*)dest, _process.get(), _preprocessConfig, _imageProcessConfig, _calibrationFiles[0], 4, _inputType); // 4 for C4 dimensionType. +// Helper::preprocessInput(_process.get(), _preprocessConfig, _calibrationFiles[0], inputTensor, _inputType); } - } - - return inputShape; -} - -void Calibration::_resizeIfNeeded(std::string filename, bool force) { - std::vector inputShape = _getInputShape(filename); - - if ((inputShape != _inputTensorDims && _featureQuantizeMethod == "KL") || force) { - _inputTensorDims = inputShape; - _interpreter->resizeTensor(_inputTensor, _inputTensorDims); - _interpreter->resizeSession(_session); - _interpreterOrigin->resizeTensor(_inputTensorOrigin, _inputTensorDims); - _interpreterOrigin->resizeSession(_sessionOrigin); + _initMaps(); } } void Calibration::_initMNNSession(const uint8_t* modelBuffer, const int bufferSize) { - _interpreterOrigin.reset(MNN::Interpreter::createFromBuffer(modelBuffer, bufferSize), MNN::Interpreter::destroy); - MNN::ScheduleConfig config; - _sessionOrigin = _interpreterOrigin->createSession(config); - _inputTensorOrigin = _interpreterOrigin->getSessionInput(_sessionOrigin, NULL); - _fake_quant_weights(); - - flatbuffers::FlatBufferBuilder builder(1024); - auto offset = MNN::Net::Pack(builder, _originalModel); - builder.Finish(offset); - int size = builder.GetSize(); - auto buffer = builder.GetBufferPointer(); - - _interpreter.reset(MNN::Interpreter::createFromBuffer(buffer, size), MNN::Interpreter::destroy); - _session = _interpreter->createSession(config); - _inputTensor = _interpreter->getSessionInput(_session, NULL); - - if (_featureQuantizeMethod == "ADMM") { - DCHECK((_calibrationFileNum * 4 * _height * _width) < (INT_MAX / 4)) << "Use Little Number of Images When Use ADMM"; - for (auto file : _calibrationFiles) { - std::vector sampleShape = _getInputShape(file); - if (_inputTensorDims.empty()) { - _inputTensorDims = sampleShape; - } - if (sampleShape != _inputTensorDims) { - MNN_ERROR("samples must have the same shape when using ADMM method for sequence inputs."); - } - } - _inputTensorDims[0] = _calibrationFileNum; - _interpreter->resizeTensor(_inputTensor, _inputTensorDims); - _interpreter->resizeSession(_session); - _interpreterOrigin->resizeTensor(_inputTensorOrigin, _inputTensorDims); - _interpreterOrigin->resizeSession(_sessionOrigin); - } - - _resizeIfNeeded(_calibrationFiles[0]); } void Calibration::_initMaps() { @@ -358,15 +485,18 @@ void Calibration::_initMaps() { if (iter != _skip_quant_ops.end()) { return false; } - for (auto t : nTensors) { + for (auto t : nTensors) { auto des = TensorUtils::getDescribe(t); if (des->index >= 0) { - _tensorMap[des->index] = t;; + _tensorMap[des->index] = t; } } if (Helper::gNotNeedFeatureOp.find(info->type()) == Helper::gNotNeedFeatureOp.end()) { int i = 0; for (auto t : nTensors) { + if (TensorUtils::getDescribe(t)->index < 0) { + continue; + } if (_featureInfo.find(t) == _featureInfo.end() && MNN::TensorUtils::getDescribe(t)->memoryType != MNN::Tensor::InsideDescribe::MEMORY_VIRTUAL) { _featureInfo[t] = std::shared_ptr( new TensorStatistic(t, _featureQuantizeMethod, opName + " input_tensor_" + flatbuffers::NumToString(i), _featureClampValue)); @@ -386,12 +516,15 @@ void Calibration::_initMaps() { for (auto t : nTensors) { auto des = TensorUtils::getDescribe(t); if (des->index >= 0) { - _tensorMap[des->index] = t;; + _tensorMap[des->index] = t; } } if (Helper::gNotNeedFeatureOp.find(info->type()) == Helper::gNotNeedFeatureOp.end()) { int i = 0; for (auto t : nTensors) { + if (TensorUtils::getDescribe(t)->index < 0) { + continue; + } if (_featureInfo.find(t) == _featureInfo.end()) { _featureInfo[t] = std::shared_ptr(new TensorStatistic(t, _featureQuantizeMethod, opName + " output_tensor_" + flatbuffers::NumToString(i), _featureClampValue)); @@ -401,51 +534,21 @@ void Calibration::_initMaps() { } return true; }; - _interpreter->runSessionWithCallBackInfo(_session, before, after); - - MNN::TensorCallBackWithInfo beforeOrigin = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { - std::string opName = info->name(); - std::vector::iterator iter = std::find(_skip_quant_ops.begin(), _skip_quant_ops.end(), opName); - if (iter != _skip_quant_ops.end()) { - return false; - } - if (Helper::gNotNeedFeatureOp.find(info->type()) == Helper::gNotNeedFeatureOp.end()) { - int i = 0; - for (auto t : nTensors) { - if (_featureInfoOrigin.find(t) == _featureInfoOrigin.end()) { - _featureInfoOrigin[t] = std::shared_ptr( - new TensorStatistic(t, _featureQuantizeMethod, opName + " input_tensor_" + flatbuffers::NumToString(i), _featureClampValue)); - } - i++; - } - } - return false; - }; - MNN::TensorCallBackWithInfo afterOrigin = [this](const std::vector& nTensors, - const MNN::OperatorInfo* info) { - std::string opName = info->name(); - std::vector::iterator iter = std::find(_skip_quant_ops.begin(), _skip_quant_ops.end(), opName); - if (iter != _skip_quant_ops.end()) { - return true; - } - if (Helper::gNotNeedFeatureOp.find(info->type()) == Helper::gNotNeedFeatureOp.end()) { - int i = 0; - for (auto t : nTensors) { - if (_featureInfoOrigin.find(t) == _featureInfoOrigin.end()) { - _featureInfoOrigin[t] = - std::shared_ptr(new TensorStatistic(t, _featureQuantizeMethod, opName + " output_tensor_" + flatbuffers::NumToString(i), _featureClampValue)); - } - i++; - } - } - return true; - }; - _interpreterOrigin->runSessionWithCallBackInfo(_sessionOrigin, beforeOrigin, afterOrigin); + Express::Executor::getGlobalExecutor()->setCallBack(std::move(before), std::move(after)); + // auto netInfo = _module->getInfo(); + // for (int k = 0; k < mInputs.size(); ++k) { + // mInputs[k] = _Convert(mInputs[k], netInfo->inputs[k].order); + // } + auto outputs = _module->onForward(mInputs); + for (auto& output_: outputs) { + output_->readMap(); + } + _featureInfoOrigin = _featureInfo; if (_featureQuantizeMethod == "KL") { // set the tensor-statistic method of input tensor as THRESHOLD_MAX - auto inputTensorStatistic = _featureInfo.find(_inputTensor); + auto inputTensorStatistic = _featureInfo.find(mInputs[0]->getTensor()); if (inputTensorStatistic != _featureInfo.end()) { inputTensorStatistic->second->setThresholdMethod(THRESHOLD_MAX); } @@ -455,21 +558,39 @@ void Calibration::_initMaps() { void Calibration::_computeFeatureMapsRange() { // feed input data according to input images int count = 0; - for (const auto& file : _calibrationFiles) { + + auto netInfo = _module->getInfo(); + for (const auto& file: _calibrationFiles) { + std::vector inputs; for (auto& iter : _featureInfo) { iter.second->setVisited(false); } - for (auto& iter : _featureInfo) { iter.second->resetUpdatedRangeFlags(); } - count++; - _resizeIfNeeded(file); - Helper::preprocessInput(_process.get(), _preprocessConfig, file, _inputTensor, _inputType); + + if (_inputType == Helper::SEQUENCE) { + inputs = getModuleInputs(file, netInfo, mInputNames, mInputShape); + for (int i = 0; i < inputs.size(); ++i) { + auto input = inputs[i]; + auto name = mInputNames[i]; + std::string fileName = file + "/" + name + ".txt"; + auto inputTensor = (MNN::Tensor*)input->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, fileName, inputTensor, _inputType); + } + } else { + auto inputTensor = (MNN::Tensor*)mInputs[0]->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, file, inputTensor, _inputType); + // auto dest = mInputs[0]->writeMap(); + // Helper::preprocessInput((float*)dest, _process.get(), _preprocessConfig, _imageProcessConfig, file, 4, _inputType); // 4 for C4 dimensionType. + } MNN::TensorCallBackWithInfo before = [&](const std::vector& nTensors, - const MNN::OperatorInfo* info) { + const MNN::OperatorInfo* info) { for (auto t : nTensors) { + if (TensorUtils::getDescribe(t)->index < 0) { + continue; + } if (_featureInfo.find(t) != _featureInfo.end()) { if (_featureInfo[t]->visited() == false) { _featureInfo[t]->updateRange(); @@ -481,6 +602,9 @@ void Calibration::_computeFeatureMapsRange() { MNN::TensorCallBackWithInfo after = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { for (auto t : nTensors) { + if (TensorUtils::getDescribe(t)->index < 0) { + continue; + } if (_featureInfo.find(t) != _featureInfo.end()) { if (_featureInfo[t]->visited() == false) { _featureInfo[t]->updateRange(); @@ -489,12 +613,10 @@ void Calibration::_computeFeatureMapsRange() { } return true; }; - - _interpreter->runSessionWithCallBackInfo(_session, before, after); - MNN_PRINT("\rComputeFeatureRange: %.2lf %%", (float)count * 100.0f / (float)_calibrationFileNum); - fflush(stdout); + Express::Executor::getGlobalExecutor()->setCallBack(std::move(before), std::move(after)); + auto outputs = _module->onForward(mInputs); + // outputs[0]->readMap(); } - MNN_PRINT("\n"); } void Calibration::_collectFeatureMapsDistribution() { @@ -502,26 +624,6 @@ void Calibration::_collectFeatureMapsDistribution() { iter.second->resetDistribution(); } // feed input data according to input images - MNN::TensorCallBackWithInfo before = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { - for (auto t : nTensors) { - if (_featureInfo.find(t) != _featureInfo.end()) { - if (_featureInfo[t]->visited() == false) { - _featureInfo[t]->updateDistribution(); - } - } - } - return true; - }; - MNN::TensorCallBackWithInfo after = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { - for (auto t : nTensors) { - if (_featureInfo.find(t) != _featureInfo.end()) { - if (_featureInfo[t]->visited() == false) { - _featureInfo[t]->updateDistribution(); - } - } - } - return true; - }; int count = 0; for (const auto& file : _calibrationFiles) { count++; @@ -533,9 +635,55 @@ void Calibration::_collectFeatureMapsDistribution() { for (auto& iter : _featureInfo) { iter.second->resetUpdatedDistributionFlag(); } - _resizeIfNeeded(file); - Helper::preprocessInput(_process.get(), _preprocessConfig, file, _inputTensor, _inputType); - _interpreter->runSessionWithCallBackInfo(_session, before, after); + auto netInfo = _module->getInfo(); + std::vector inputs; + // Load inputs + if (_inputType == Helper::SEQUENCE) { + inputs = getModuleInputs(file, netInfo, mInputNames, mInputShape); + for (int i = 0; i < inputs.size(); ++i) { + auto input = inputs[i]; + auto name = mInputNames[i]; + std::string fileName = file + "/" + name + ".txt"; + auto inputTensor = (MNN::Tensor*)input->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, fileName, inputTensor, _inputType); + } + } else { + auto inputTensor = (MNN::Tensor*)mInputs[0]->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, file, inputTensor, _inputType); + // auto dest = mInputs[0]->writeMap(); + // Helper::preprocessInput((float*)dest, _process.get(), _preprocessConfig, _imageProcessConfig, file, 4, _inputType); // 4 for C4 dimensionType. + } + + MNN::TensorCallBackWithInfo before = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { + for (auto t : nTensors) { + if (TensorUtils::getDescribe(t)->index < 0) { + continue; + } + if (_featureInfo.find(t) != _featureInfo.end()) { + if (_featureInfo[t]->visited() == false) { + _featureInfo[t]->updateDistribution(); + } + } + } + return true; + }; + MNN::TensorCallBackWithInfo after = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { + for (auto t : nTensors) { + if (TensorUtils::getDescribe(t)->index < 0) { + continue; + } + if (_featureInfo.find(t) != _featureInfo.end()) { + if (_featureInfo[t]->visited() == false) { + _featureInfo[t]->updateDistribution(); + } + } + } + return true; + }; + + Express::Executor::getGlobalExecutor()->setCallBack(std::move(before), std::move(after)); + auto outputs = _module->onForward(mInputs); + // outputs[0]->readMap(); MNN_PRINT("\rCollectFeatureDistribution: %.2lf %%", (float)count * 100.0f / (float)_calibrationFileNum); fflush(stdout); @@ -557,21 +705,35 @@ void Calibration::_computeFeatureScaleKL() { void Calibration::_computeFeatureScaleADMM() { // feed input data according to input images - int count = 0; - std::vector oneImageTensorDims = _inputTensorDims; - oneImageTensorDims[0] = 1; - auto inputTensorDataFormat = MNN::TensorUtils::getDescribe(_inputTensor)->dimensionFormat; + int count = 0; + auto netInfo = _module->getInfo(); + std::vector inputs(mInputNames.size()); + std::vector inputTensors(mInputNames.size()); + for (int i = 0; i < inputs.size(); ++i) { + auto shape = mInputShape[mInputNames[i]]; + shape[0] = _calibrationFileNum; + inputs[i] = _Input(shape, netInfo->inputs[i].order, netInfo->inputs[i].type); + inputTensors[i] = inputs[i]->getTensor(); + } auto dimType = MNN::Tensor::CAFFE_C4; - if (inputTensorDataFormat == MNN::MNN_DATA_FORMAT_NHWC) { + if (netInfo->inputs[0].order == NHWC) { dimType = MNN::Tensor::TENSORFLOW; } - for (const auto& file : _calibrationFiles) { - auto curPtr = _inputTensor->host() + count * _inputTensor->stride(0); - std::shared_ptr tensorWarp( - MNN::Tensor::create(oneImageTensorDims, _inputTensor->getType(), curPtr, dimType), MNN::Tensor::destroy); - Helper::preprocessInput(_process.get(), _preprocessConfig, file, tensorWarp.get(), _inputType); - + if (_inputType == Helper::SEQUENCE) { + for (int j = 0; j < inputs.size(); ++j) { + auto name = mInputNames[j]; + std::string fileName = file + "/" + name + ".txt"; + auto inputPtr = inputTensors[j]->host() + count * inputTensors[j]->stride(0); + std::shared_ptr tensor(MNN::Tensor::create(mInputShape[name], netInfo->inputs[j].type, inputPtr, dimType), MNN::Tensor::destroy); + Helper::preprocessInput(_process.get(), _preprocessConfig, fileName, tensor.get(), _inputType); + } + } else { + auto inputPtr = inputTensors[0]->host() + count * inputTensors[0]->stride(0); + auto name = mInputNames[0]; + std::shared_ptr tensor(MNN::Tensor::create(mInputShape[name], netInfo->inputs[0].type, inputPtr, dimType), MNN::Tensor::destroy); + Helper::preprocessInput(_process.get(), _preprocessConfig, file, tensor.get(), _inputType); + } count++; MNN_PRINT("\rProcessCalibrationFiles: %.2lf %%", (float)count * 100.0f / (float)_calibrationFileNum); fflush(stdout); @@ -612,8 +774,8 @@ void Calibration::_computeFeatureScaleADMM() { } return true; }; - - _interpreter->runSessionWithCallBackInfo(_session, before, after); + Express::Executor::getGlobalExecutor()->setCallBack(std::move(before), std::move(after)); + _module->onForward(inputs); MNN_PRINT("\n"); } @@ -698,6 +860,9 @@ void Calibration::_insertScale() { } auto inputTensor = _tensorMap[op->inputIndexes[0]]; auto outputTensor = _tensorMap[op->outputIndexes[0]]; + if (inputTensor == nullptr || outputTensor == nullptr) { + continue; + } // below is Conv/DepthwiseConv weight quant const float inputScale = _scales[inputTensor].first; const float outputScale = _scales[outputTensor].first; @@ -744,18 +909,10 @@ void Calibration::_insertScale() { } void Calibration::_computeQuantError() { - int count = 0; std::map> overflowRatiosMap; std::map> tensorCosDistanceMap; - - for (const auto& file : _calibrationFiles) { - count++; - _resizeIfNeeded(file, true); - Helper::preprocessInput(_process.get(), _preprocessConfig, file, _inputTensor, _inputType); - - std::map> fakeQuantedFeatures; - - MNN::TensorCallBackWithInfo before = [&](const std::vector& nTensors, + std::map> fakeQuantedFeatures; + MNN::TensorCallBackWithInfo before = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { if (info->type() == "Raster") { return true; @@ -770,64 +927,83 @@ void Calibration::_computeQuantError() { } } return true; - }; - MNN::TensorCallBackWithInfo after = [&](const std::vector& nTensors, + }; + MNN::TensorCallBackWithInfo after = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { - for (auto t : nTensors) { - if (_featureInfo.find(t) != _featureInfo.end()) { - if (_featureInfo[t]->visited() == false) { - auto dequantFeatureAndOverflowRatio = _featureInfo[t]->fakeQuantFeature(); - fakeQuantedFeatures[_featureInfo[t]->name()] = dequantFeatureAndOverflowRatio.first; - overflowRatiosMap[_featureInfo[t]->name()].emplace_back(dequantFeatureAndOverflowRatio.second); - } + for (auto t : nTensors) { + if (_featureInfo.find(t) != _featureInfo.end()) { + if (_featureInfo[t]->visited() == false) { + auto dequantFeatureAndOverflowRatio = _featureInfo[t]->fakeQuantFeature(); + fakeQuantedFeatures[_featureInfo[t]->name()] = dequantFeatureAndOverflowRatio.first; + overflowRatiosMap[_featureInfo[t]->name()].emplace_back(dequantFeatureAndOverflowRatio.second); } } - return true; - }; - - for (auto& iter : _featureInfo) { - iter.second->setVisited(false); } + return true; + }; - _interpreter->runSessionWithCallBackInfo(_session, before, after); - - Helper::preprocessInput(_process.get(), _preprocessConfig, file, _inputTensorOrigin, _inputType); - - MNN::TensorCallBackWithInfo beforeOrigin = [&](const std::vector& nTensors, + MNN::TensorCallBackWithInfo beforeOrigin = [&](const std::vector& nTensors, const MNN::OperatorInfo* info) { - if (info->type() == "Raster") { - return true; - } - for (auto t : nTensors) { - if (_featureInfoOrigin.find(t) != _featureInfoOrigin.end()) { - if (_featureInfoOrigin[t]->visited() == false) { - auto name = _featureInfoOrigin[t]->name(); - float cosDis = _featureInfoOrigin[t]->computeDistance(fakeQuantedFeatures[name]); - tensorCosDistanceMap[name].emplace_back(cosDis); - } + if (info->type() == "Raster") { + return true; + } + for (auto t : nTensors) { + if (_featureInfoOrigin.find(t) != _featureInfoOrigin.end()) { + if (_featureInfoOrigin[t]->visited() == false) { + auto name = _featureInfoOrigin[t]->name(); + float cosDis = _featureInfoOrigin[t]->computeDistance(fakeQuantedFeatures[name]); + tensorCosDistanceMap[name].emplace_back(cosDis); } } - return true; - }; - MNN::TensorCallBackWithInfo afterOrigin = [&](const std::vector& nTensors, - const MNN::OperatorInfo* info) { - for (auto t : nTensors) { - if (_featureInfoOrigin.find(t) != _featureInfoOrigin.end()) { - if (_featureInfoOrigin[t]->visited() == false) { - auto name = _featureInfoOrigin[t]->name(); - float cosDis = _featureInfoOrigin[t]->computeDistance(fakeQuantedFeatures[name]); - tensorCosDistanceMap[name].emplace_back(cosDis); - } + } + return true; + }; + MNN::TensorCallBackWithInfo afterOrigin = [&](const std::vector& nTensors, + const MNN::OperatorInfo* info) { + for (auto t : nTensors) { + if (_featureInfoOrigin.find(t) != _featureInfoOrigin.end()) { + if (_featureInfoOrigin[t]->visited() == false) { + auto name = _featureInfoOrigin[t]->name(); + float cosDis = _featureInfoOrigin[t]->computeDistance(fakeQuantedFeatures[name]); + tensorCosDistanceMap[name].emplace_back(cosDis); } } - return true; - }; + } + return true; + }; + int count = 0; + for (const auto& file : _calibrationFiles) { + count++; + + for (auto& iter : _featureInfo) { + iter.second->setVisited(false); + } for (auto& iter : _featureInfoOrigin) { iter.second->setVisited(false); } - - _interpreterOrigin->runSessionWithCallBackInfo(_sessionOrigin, beforeOrigin, afterOrigin); + std::vector inputs(mInputNames.size()); + auto netInfo = _module->getInfo(); + if (_inputType == Helper::SEQUENCE) { + inputs = getModuleInputs(file, netInfo, mInputNames, mInputShape); + for (int i = 0; i < inputs.size(); ++i) { + auto input = inputs[i]; + auto name = mInputNames[i]; + std::string fileName = file + "/" + name + ".txt"; + auto inputTensor = (MNN::Tensor*)input->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, fileName, inputTensor, _inputType); + } + } else { + inputs.resize(1); + inputs[0] = _Input(netInfo->inputs[0].dim, netInfo->inputs[0].order, netInfo->inputs[0].type); + inputs[0] = _Convert(inputs[0], netInfo->inputs[0].order); + auto inputTensor = (MNN::Tensor*)inputs[0]->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, file, inputTensor, _inputType); + } + Express::Executor::getGlobalExecutor()->setCallBack(std::move(before), std::move(after)); + _module->onForward(inputs); + Express::Executor::getGlobalExecutor()->setCallBack(std::move(beforeOrigin), std::move(afterOrigin)); + _moduleOrigin->onForward(inputs); MNN_PRINT("\rcomputeDistance: %.2lf %%", (float)count * 100.0f / (float)_calibrationFileNum); fflush(stdout); @@ -856,13 +1032,9 @@ void Calibration::_quantizeModelEMA() { } auto inputOutputs = Variable::getInputAndOutput(varMap); - auto inputs = Variable::mapToSequence(inputOutputs.first); - auto outputs = Variable::mapToSequence(inputOutputs.second); - if (inputs.size() != 1) { - MNN_ERROR("Only support input size = 1\n"); - return; - } - auto originInfo = inputs[0]->getInfo(); + auto varInputs = Variable::mapToSequence(inputOutputs.first); + auto varOutputs = Variable::mapToSequence(inputOutputs.second); + auto originInfo = varInputs[0]->getInfo(); auto originFormat = NC4HW4; auto originType = halide_type_of(); std::vector originDims; @@ -871,14 +1043,14 @@ void Calibration::_quantizeModelEMA() { originDims = originInfo->dim; originType = originInfo->type; } - std::shared_ptr model(NN::extract(inputs, outputs, true), Module::destroy); - NN::turnQuantize(model.get(), _quant_bits, NN::PerTensor, NN::MovingAverage, _winogradOpt); + _module.reset(NN::extract(varInputs, varOutputs, true), Module::destroy); + NN::turnQuantize(_module.get(), _quant_bits, NN::PerTensor, NN::MovingAverage, _winogradOpt); auto exe = Executor::getGlobalExecutor(); BackendConfig config; - exe->setGlobalExecutorConfig(MNN_FORWARD_CPU, config, 2); + exe->setGlobalExecutorConfig(MNN_FORWARD_CPU, config, 1); - std::shared_ptr solver(new SGD(model)); + std::shared_ptr solver(new SGD(_module)); solver->setLearningRate(1e-5); solver->setMomentum(0.9f); solver->setWeightDecay(0.00004f); @@ -889,95 +1061,102 @@ void Calibration::_quantizeModelEMA() { MNN_ERROR("_calibrationFileNum %d < batch size %d, set batch size as %d\n", _calibrationFileNum, _batch, _calibrationFileNum); _batch = _calibrationFileNum; } - DataLoader* trainDataLoader = nullptr; - std::shared_ptr tempInputTensor = nullptr; - if (_inputType == Helper::InputType::IMAGE) { - auto converImagesToFormat = _imageProcessConfig.destFormat; - int resizeHeight = _preprocessConfig.targetHeight; - int resizeWidth = _preprocessConfig.targetWidth; - std::vector means, scales; - for (int i = 0; i < 4; i++) { - means.emplace_back(_imageProcessConfig.mean[i]); - scales.emplace_back(_imageProcessConfig.normal[i]); - } - std::vector cropFraction = {_preprocessConfig.centerCropHeight, _preprocessConfig.centerCropWidth}; // center crop fraction for height and width - bool centerOrRandomCrop = false; // true for random crop - std::shared_ptr datasetConfig(ImageDataset::ImageConfig::create(converImagesToFormat, resizeHeight, resizeWidth, scales, means, cropFraction, centerOrRandomCrop)); - auto trainDataset = ImageNoLabelDataset::create(_calibrationFilePath, datasetConfig.get()); - - const int trainBatchSize = _batch; - const int trainNumWorkers = 0; - trainDataLoader = trainDataset.createLoader(trainBatchSize, true, false, trainNumWorkers); - trainDataLoader->reset(); - } else { - flatbuffers::FlatBufferBuilder builder(1024); - auto offset = MNN::Net::Pack(builder, _originalModel); - builder.Finish(offset); - int size = builder.GetSize(); - auto buffer = builder.GetBufferPointer(); - _interpreter.reset(MNN::Interpreter::createFromBuffer(buffer, size), MNN::Interpreter::destroy); - MNN::ScheduleConfig config; - _session = _interpreter->createSession(config); - _inputTensor = _interpreter->getSessionInput(_session, NULL); - - _getInputShape(_calibrationFiles[0]); - std::vector tempData(_batch * _channels * _height, 0.0f); - tempInputTensor.reset(MNN::Tensor::create({_batch, _channels, _height}, halide_type_of(), tempData.data(), MNN::Tensor::CAFFE), MNN::Tensor::destroy); - } - const int trainIterations = _calibrationFileNum / _batch; - model->clearCache(); + const int trainIterations = _calibrationFileNum / _batch; + _module->clearCache(); exe->gc(Executor::FULL); - model->setIsTraining(true); - for (int i = 0; i < trainIterations; i++) { - VARP input; - if (_inputType == Helper::InputType::IMAGE) { - auto trainData = trainDataLoader->next(); - auto example = trainData[0]; - input = example.first[0]; + _module->setIsTraining(true); + for (int it = 0; it < trainIterations; it++) { + std::vector inputs(varInputs.size()); // inputs[i].dim=[batch, c, h, w] + int indicesStart = it * _batch; + int indicesEnd = indicesStart + _batch; + // Init batch size inputs + if (_inputType == Helper::IMAGE) { + inputs[0] = _Input({_batch, originDims[1], originDims[2], originDims[3]}, originFormat, originType); } else { - for (auto& file : _calibrationFiles) { - for (int j = 0; j < _batch; j++) { - auto curPtr = tempInputTensor->host() + j * tempInputTensor->stride(0); - std::shared_ptr tensorWarp(MNN::Tensor::create({1, _channels, _height}, _inputTensor->getType(), curPtr, MNN::Tensor::CAFFE), MNN::Tensor::destroy); - Helper::preprocessInput(_process.get(), _preprocessConfig, file, tensorWarp.get(), _inputType); + for (auto& input: inputs) { + input = _Input({_batch, originDims[1], originDims[2], originDims[3]}, originFormat, originType); + } + } + // Compose batch input + for (int k = indicesStart; k < indicesEnd; ++k) { + const auto file = _calibrationFiles[k]; + if (_inputType == Helper::SEQUENCE) { + std::map> dyInputShape = mInputShape; + std::string jsonFile = file + "/" + "input.json"; + std::ifstream f(jsonFile.c_str()); + if (f.is_open()) { + rapidjson::Document document; + std::ostringstream json_os; + json_os << f.rdbuf(); + document.Parse(json_os.str().c_str()); + if (document.HasParseError()) { + MNN_ERROR("Invalid json: %s\n", jsonFile.c_str()); + } + auto cfgObj = document.GetObject(); + if (cfgObj.HasMember("inputs")) { + auto inputsInfo = document["inputs"].GetArray(); + for (auto iter = inputsInfo.begin(); iter !=inputsInfo.end(); iter++) { + auto obj = iter->GetObject(); + std::string name = obj["name"].GetString(); + if (obj.HasMember("shape")) { + auto dims = obj["shape"].GetArray(); + std::vector shapes; + for (auto iter = dims.begin(); iter != dims.end(); iter++) { + shapes.emplace_back(iter->GetInt()); + } + dyInputShape[name] = shapes; + dyInputShape[name][0] = _batch; + } + } + } } - input = _Input({_batch, _channels, _height}, MNN::Express::Dimensionformat::NCHW, halide_type_of()); - auto inputPtr = input->writeMap(); - auto tempInputPtr = tempInputTensor->host(); - for (int j = 0; j < _batch * _channels * _height; j++) { - inputPtr[j] = tempInputPtr[j]; + + for (int i = 0; i < inputs.size(); ++i) { + auto name = varInputs[i]->name(); + auto input = _Input(dyInputShape[name], varInputs[i]->getInfo()->order, varInputs[i]->getInfo()->type); + std::string fileName = file + "/" + name + ".txt"; + + auto inputTensor = (MNN::Tensor*)input->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, fileName, inputTensor, _inputType); + ::memcpy(input->writeMap(), inputTensor->host(), inputTensor->elementSize() * sizeof(float)); + inputs[i] = input; } + } else { + auto singleInput = _Input(originDims, originFormat, originType); + auto inputTensor = (MNN::Tensor*)singleInput->getTensor(); + Helper::preprocessInput(_process.get(), _preprocessConfig, file, inputTensor, _inputType); + ::memcpy(inputs[0]->writeMap() + k * inputTensor->elementSize(), inputTensor->host(), inputTensor->elementSize() * sizeof(float)); + } } - auto predicts = model->onForward({_Convert(input, originFormat)}); - for (auto& output : predicts) { + auto predicts = _module->onForward(inputs); + for (auto &output: predicts) { auto ptr = output->readMap(); } - MNN_PRINT("\rquantize with EMA: %.2lf %%", (i + 1) * 100.0f / trainIterations); + MNN_PRINT("\rquantize with EMA: %.2lf %%", (it + 1) * 100.0f / trainIterations); fflush(stdout); solver->step(_Scalar(0.0f)); } MNN_PRINT("\n"); - model->setIsTraining(false); + _module->setIsTraining(false); exe->gc(Executor::PART); - VARP forwardInput = nullptr; - if (originInfo != nullptr && originDims.size() > 0) { - forwardInput = _Input(originDims, originFormat, originType); - } else { - if (_inputType == Helper::InputType::IMAGE) { - forwardInput = _Input({1, _channels, _preprocessConfig.targetHeight, _preprocessConfig.targetWidth}, NC4HW4); - } else { - forwardInput = _Input({1, _channels, _height}, NC4HW4); - } + std::vector inputsForward; + inputsForward.resize(varInputs.size()); + for (int i = 0; i < inputsForward.size(); ++i) { + auto name = varInputs[i]->name(); + auto input = _Input(mInputShape[name], varInputs[i]->getInfo()->order, varInputs[i]->getInfo()->type); + input->setName(name); + inputsForward[i] = input; } - forwardInput->setName(inputs[0]->name()); - auto predicts = model->onForward({forwardInput}); + + auto predicts = _module->onForward(inputsForward); + Transformer::turnModelToInfer()->onExecute(predicts); for (int i = 0; i < predicts.size(); i++) { - predicts[i]->setName(outputs[i]->name()); + predicts[i]->setName(varOutputs[i]->name()); } Variable::save(predicts, _destModelFile.c_str()); ConvertToFullQuant::convert(_destModelFile); @@ -1213,11 +1392,10 @@ void Calibration::ComputeUnaryBuffer(MNN::NetT* net) { if (type == UnaryOpOperation_ABS || type == UnaryOpOperation_NEG || type == UnaryOpOperation_SIGN) { continue; } - op->main.AsUnaryOp()->tableInt8.resize(255); - auto unaryParam = op->main.AsUnaryOp()->tableInt8.data(); auto outputId = op->outputIndexes[0]; if (describes.find(outputId) == describes.end()) { + MNN_PRINT("Can't find input extraTensorDescribe for %s\n", op->name.c_str()); continue; } auto unaryDes = describes.find(outputId)->second; @@ -1225,8 +1403,11 @@ void Calibration::ComputeUnaryBuffer(MNN::NetT* net) { float outZero = unaryDes->quantInfo->zero; auto inputId = op->inputIndexes[0]; if (describes.find(inputId) == describes.end()) { - MNN_ERROR("Can't find extraTensorDescribe for %s\n", op->name.c_str()); + MNN_PRINT("Can't find input extraTensorDescribe for %s\n", op->name.c_str()); + continue; } + op->main.AsUnaryOp()->tableInt8.resize(255); + auto unaryParam = op->main.AsUnaryOp()->tableInt8.data(); unaryDes = describes.find(inputId)->second; float inpScale = unaryDes->quantInfo->scale; float inpZero = unaryDes->quantInfo->zero; diff --git a/tools/quantization/calibration.hpp b/tools/quantization/calibration.hpp index 0c76316c7..6546ba57a 100644 --- a/tools/quantization/calibration.hpp +++ b/tools/quantization/calibration.hpp @@ -14,6 +14,7 @@ #include #include #include "TensorStatistic.hpp" +#include #include "MNN_generated.h" #include "Helper.hpp" #include "logkit.h" @@ -56,6 +57,13 @@ class Calibration { std::string _destModelFile; MNN::CV::ImageProcess::Config _imageProcessConfig; std::vector _calibrationFiles; + std::vector mCalibrationDatasetDir; + std::vector mInputNames; + std::vector mOutputNames; + std::map mInputInfo; + std::map> mInputShape; + std::vector mInputs; + std::shared_ptr mBackend; // Tensor and Info std::map> _featureInfo; @@ -65,15 +73,12 @@ class Calibration { // The scale results std::map> _scales; - std::shared_ptr _interpreter; // keep mnn forward information - MNN::Session* _session; - MNN::Tensor* _inputTensor; + std::vector mInputTensors; std::vector _inputTensorDims; - std::shared_ptr _interpreterOrigin; - MNN::Session* _sessionOrigin; - MNN::Tensor* _inputTensorOrigin; + std::shared_ptr _module; + std::shared_ptr _moduleOrigin; std::string _featureQuantizeMethod = "KL"; std::string _weightQuantizeMethod = "MAX_ABS"; diff --git a/transformers/diffusion/README.md b/transformers/diffusion/README.md new file mode 100644 index 000000000..42d247ca8 --- /dev/null +++ b/transformers/diffusion/README.md @@ -0,0 +1,45 @@ +# Diffusion使用方法 + +## 模型支持与下载 + +[Download-runwayml/stable-diffusion-v1-5]: +https://huggingface.co/runwayml/stable-diffusion-v1-5/tree/main +[Download-IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1]: +https://huggingface.co/IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1/tree/main + +## 模型转换 +### 将Huggingface的Stable Diffusion模型 转为onnx模型 +python export/onnx_export.py \ + --model_path hf_sd_load_path \ + --output_path onnx_save_path + +### 将onnx模型转为mnn模型 +新建diffusion mnn模型文件夹，将转好的mnn文件放在该文件夹下。 +./MNNConvert -f ONNX --modelFile onnx_save_path/text_encoder/model.onnx --MNNModel mnn_save_path/text_encoder.mnn --weightQuantBits 8 --bizCode biz +./MNNConvert -f ONNX --modelFile onnx_save_path/unet/model.onnx --MNNModel mnn_save_path/unet.mnn --transformerFuse --weightQuantBits 8 --bizCode biz +./MNNConvert -f ONNX --modelFile onnx_save_path/vae_decoder/model.onnx --keepInputFormat --MNNModel mnn_save_path/vae_decoder.mnn --weightQuantBits 8 --bizCode biz + +## 编译Diffusion Demo +### Linux/MAC/Windows上 +cmake .. -DMNN_BUILD_DIFFUSION=ON -DMNN_BUILD_OPENCV=ON -DMNN_IMGCODECS=ON -DMNN_OPENCL=ON -DMNN_SEP_BUILD=OFF -DMNN_SUPPORT_TRANSFORMER_FUSE=ON + +### Android上 +cd project/android/build +../build_64.sh -DMNN_BUILD_DIFFUSION=ON -DMNN_BUILD_OPENCV=ON -DMNN_IMGCODECS=ON -DMNN_OPENCL=ON -DMNN_SEP_BUILD=OFF -DMNN_SUPPORT_TRANSFORMER_FUSE=ON + +## 运行Diffusion Demo +./diffusion_demo +其中，resource_path 就是mnn模型文件的路径，除了mnn文件，还需要 +（1）将MNN目录transformers/diffusion/scheduler/alphas.txt文件拷贝到该文件夹下。 +（2）针对stable-diffusion-v1-5模型需要将huggingfacetokenizer目录下merges.txt和vocab.json拷贝到该文件夹中。针对Taiyi-Stable-Diffusion模型需要将huggingfacetokenizer目录下vocab.txt拷贝到该文件夹中。 + +model_type是目前支持的两种diffusion模型的类别。如果是stable-diffusion-v1-5模型设为0，如果是Taiyi-Stable-Diffusion模型设为1。 + +output_image_name是生成图片的名字，默认图片位置在当前运行目录下。 + +input_text是文生图的prompt，如果是stable-diffusion-v1-5模型建议英文prompt，如果是Taiyi-Stable-Diffusion建议中文prompt。 + +运行指令例如: +./diffusion_demo mnn_save_path 0 demo.jpg "a cute cat" +./diffusion_demo mnn_save_path 1 demo.jpg "一只可爱的猫" + diff --git a/transformers/diffusion/export/onnx_export.py b/transformers/diffusion/export/onnx_export.py new file mode 100644 index 000000000..21f05e83b --- /dev/null +++ b/transformers/diffusion/export/onnx_export.py @@ -0,0 +1,212 @@ +# Copyright 2024 The HuggingFace Team. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +import shutil +from pathlib import Path + +import torch +from torch.onnx import export + +import onnx +from diffusers import OnnxStableDiffusionPipeline, StableDiffusionPipeline +from packaging import version + + +is_torch_less_than_1_11 = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11") + + +def onnx_export( + model, + model_args: tuple, + output_path: Path, + ordered_input_names, + output_names, + dynamic_axes, + opset, + use_external_data_format=False, +): + output_path.parent.mkdir(parents=True, exist_ok=True) + # PyTorch deprecated the `enable_onnx_checker` and `use_external_data_format` arguments in v1.11, + # so we check the torch version for backwards compatibility + if is_torch_less_than_1_11: + export( + model, + model_args, + f=output_path.as_posix(), + input_names=ordered_input_names, + output_names=output_names, + dynamic_axes=dynamic_axes, + do_constant_folding=True, + use_external_data_format=use_external_data_format, + enable_onnx_checker=True, + opset_version=opset, + ) + else: + export( + model, + model_args, + f=output_path.as_posix(), + input_names=ordered_input_names, + output_names=output_names, + dynamic_axes=dynamic_axes, + do_constant_folding=True, + opset_version=opset, + ) + + +@torch.no_grad() +def convert_models(model_path: str, output_path: str, opset: int, fp16: bool = False): + dtype = torch.float16 if fp16 else torch.float32 + if fp16 and torch.cuda.is_available(): + device = "cuda" + elif fp16 and not torch.cuda.is_available(): + raise ValueError("`float16` model export is only supported on GPUs with CUDA") + else: + device = "cpu" + device = "cpu" + pipeline = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=dtype).to(device) + output_path = Path(output_path) + + # TEXT ENCODER + num_tokens = pipeline.text_encoder.config.max_position_embeddings + text_hidden_size = pipeline.text_encoder.config.hidden_size + text_input = pipeline.tokenizer( + "A sample prompt", + padding="max_length", + max_length=pipeline.tokenizer.model_max_length, + truncation=True, + return_tensors="pt", + ) + onnx_export( + pipeline.text_encoder, + # casting to torch.int32 until the CLIP fix is released: https://github.com/huggingface/transformers/pull/18515/files + model_args=(text_input.input_ids.to(device=device, dtype=torch.int32)), + output_path=output_path / "text_encoder" / "model.onnx", + ordered_input_names=["input_ids"], + output_names=["last_hidden_state", "pooler_output"], + dynamic_axes={ + "input_ids": {0: "batch", 1: "sequence"}, + }, + opset=opset, + ) + del pipeline.text_encoder + + # UNET + unet_in_channels = pipeline.unet.config.in_channels + unet_sample_size = pipeline.unet.config.sample_size + unet_path = output_path / "unet" / "model.onnx" + onnx_export( + pipeline.unet, + model_args=( + torch.randn(2, unet_in_channels, unet_sample_size, unet_sample_size).to(device=device, dtype=dtype), + torch.randn(2).to(device=device, dtype=torch.int32), + torch.randn(2, num_tokens, text_hidden_size).to(device=device, dtype=dtype), + # False, + ), + output_path=unet_path, + ordered_input_names=["sample", "timestep", "encoder_hidden_states", "return_dict"], + output_names=["out_sample"], # has to be different from "sample" for correct tracing + dynamic_axes={ + "sample": {0: "batch", 1: "channels", 2: "height", 3: "width"}, + "timestep": {0: "batch"}, + "encoder_hidden_states": {0: "batch", 1: "sequence"}, + }, + opset=opset, + use_external_data_format=True, # UNet is > 2GB, so the weights need to be split + ) + unet_model_path = str(unet_path.absolute().as_posix()) + unet_dir = os.path.dirname(unet_model_path) + unet = onnx.load(unet_model_path) + # clean up existing tensor files + shutil.rmtree(unet_dir) + os.mkdir(unet_dir) + # collate external tensor files into one + onnx.save_model( + unet, + unet_model_path, + save_as_external_data=True, + all_tensors_to_one_file=True, + location="weights.pb", + convert_attribute=False, + ) + del pipeline.unet + + # VAE ENCODER + vae_encoder = pipeline.vae + vae_in_channels = vae_encoder.config.in_channels + vae_sample_size = vae_encoder.config.sample_size + # need to get the raw tensor output (sample) from the encoder + vae_encoder.forward = lambda sample, return_dict: vae_encoder.encode(sample, return_dict)[0].sample() + onnx_export( + vae_encoder, + model_args=( + torch.randn(1, vae_in_channels, vae_sample_size, vae_sample_size).to(device=device, dtype=dtype), + False, + ), + output_path=output_path / "vae_encoder" / "model.onnx", + ordered_input_names=["sample", "return_dict"], + output_names=["latent_sample"], + dynamic_axes={ + "sample": {0: "batch", 1: "channels", 2: "height", 3: "width"}, + }, + opset=opset, + ) + + # VAE DECODER + vae_decoder = pipeline.vae + vae_latent_channels = vae_decoder.config.latent_channels + vae_out_channels = vae_decoder.config.out_channels + # forward only through the decoder part + vae_decoder.forward = vae_encoder.decode + onnx_export( + vae_decoder, + model_args=( + torch.randn(1, vae_latent_channels, unet_sample_size, unet_sample_size).to(device=device, dtype=dtype), + False, + ), + output_path=output_path / "vae_decoder" / "model.onnx", + ordered_input_names=["latent_sample", "return_dict"], + output_names=["sample"], + dynamic_axes={ + "latent_sample": {0: "batch", 1: "channels", 2: "height", 3: "width"}, + }, + opset=opset, + ) + del pipeline.vae + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + + parser.add_argument( + "--model_path", + type=str, + required=True, + help="Path to the `diffusers` checkpoint to convert (either a local directory or on the Hub).", + ) + + parser.add_argument("--output_path", type=str, required=True, help="Path to the output model.") + + parser.add_argument( + "--opset", + default=14, + type=int, + help="The version of the ONNX operator set to use.", + ) + parser.add_argument("--fp16", action="store_true", default=False, help="Export the models in `float16` mode") + + args = parser.parse_args() + + convert_models(args.model_path, args.output_path, args.opset, args.fp16) diff --git a/transformers/diffusion/main.cpp b/transformers/diffusion/main.cpp index 23f3f33c2..4cbb03d1e 100644 --- a/transformers/diffusion/main.cpp +++ b/transformers/diffusion/main.cpp @@ -3,15 +3,16 @@ int main(int argc, const char* argv[]) { if (argc < 3) { - printf("Usage: ./diffusion_demo "); + printf("Usage: ./diffusion_demo \n"); return 0; } auto resource_path = argv[1]; - auto img_name = argv[2]; + auto model_type = (diffusion::DiffusionModelType)atoi(argv[2]); + auto img_name = argv[3]; std::string input_text; - for (int i = 3; i < argc; ++i) { + for (int i = 4; i < argc; ++i) { input_text += argv[i]; if (i < argc - 1) { input_text += " "; @@ -19,10 +20,18 @@ int main(int argc, const char* argv[]) { } printf("model resource path: %s\n", resource_path); + if(model_type == diffusion::STABLE_DIFFUSION_1_5) { + printf("model resourc is stable diffusion 1.5\n"); + } else if (model_type == diffusion::STABLE_DIFFUSION_TAIYI_CHINESE) { + printf("model resourc is stable diffusion taiyi chinese version\n"); + } else { + printf("model type: %d not supported, please check\n", (int)model_type); + } printf("output img_name: %s\n", img_name); printf("input texts: %s\n", input_text.c_str()); + - diffusion::Pipeline pipeline(resource_path); + diffusion::Pipeline pipeline(resource_path, model_type); pipeline.run(input_text, img_name); return 0; } diff --git a/transformers/diffusion/pipeline.cpp b/transformers/diffusion/pipeline.cpp index 57a16443e..32d794684 100644 --- a/transformers/diffusion/pipeline.cpp +++ b/transformers/diffusion/pipeline.cpp @@ -18,9 +18,6 @@ #include #endif -//#define TEXT_MAX_LEN 512 // Taiyi_SD -#define TEXT_MAX_LEN 77 // SD_1.5 - //#define MNN_DUMP_DATA using namespace CV; @@ -55,7 +52,12 @@ void display_progress(int cur, int total){ fflush(stdout); } -Pipeline::Pipeline(std::string modelPath) : mModelPath(modelPath) { +Pipeline::Pipeline(std::string modelPath, DiffusionModelType modelType) : mModelPath(modelPath), mModelType(modelType) { + if(modelType == STABLE_DIFFUSION_1_5) { + mMaxTextLen = 77; + } else if(modelType == diffusion::STABLE_DIFFUSION_TAIYI_CHINESE) { + mMaxTextLen = 512; + } std::ifstream alphaFile(modelPath + "/alphas.txt"); int index = 0; float alpha; @@ -70,25 +72,28 @@ Pipeline::Pipeline(std::string modelPath) : mModelPath(modelPath) { 161, 141, 121, 101, 81, 61, 41, 21, 1 }; mTimeSteps = { // 20 steps - 951, 901, 901, 851, 801, 751, 701, 651, 601, 551, 501, 451, - 401, 351, 301, 251, 201, 151, 101, 51, 1 + 951, 901, 901, 851, 801, 751, 701, 651, 601, 551, 501, 451, + 401, 351, 301, 251, 201, 151, 101, 51, 1 }; + mTimeSteps = { // 5 steps + 801, 601, 601, + 401, 201, 1 + }; #endif mTimeSteps = { - 801, 601, 601, - 401, 201, 1 + 951, 901, 901, 851, 801, 751, 701, 651, 601, 551, 501, 451, + 401, 351, 301, 251, 201, 151, 101, 51, 1 }; } bool Pipeline::load_modules(std::string modelPath) { AUTOTIME; - ScheduleConfig config; BackendConfig backendConfig; // config.type = MNN_FORWARD_CPU; config.type = MNN_FORWARD_OPENCL; - config.numThread = 65; - backendConfig.precision = BackendConfig::Precision_Normal; + config.mode = MNN_GPU_MEMORY_BUFFER | MNN_GPU_TUNING_FAST; + backendConfig.precision = BackendConfig::Precision_Low; backendConfig.memory = BackendConfig::Memory_Low; config.backendConfig = &backendConfig; @@ -98,30 +103,52 @@ bool Pipeline::load_modules(std::string modelPath) { // module_config.rearrange = true; runtime_manager_.reset(Executor::RuntimeManager::createRuntimeManager(config)); - // if (config.type == MNN_FORWARD_OPENCL) { - // const char* cacheFileName = ".tempcache"; - // runtime_manager_->setCache(cacheFileName); - // } + if (config.type == MNN_FORWARD_OPENCL) { + const char* cacheFileName = ".tempcache"; + runtime_manager_->setCache(cacheFileName); + } + + mLatentVar = _Input({1, 4, 64, 64}, NCHW, halide_type_of()); + mPromptVar = _Input({2, mMaxTextLen}, NCHW, halide_type_of()); + mTimestepVar = _Input({1}, NCHW, halide_type_of()); + mSampleVar = _Concat({mLatentVar, mLatentVar}, 0); + printf("Model loading and initilizing...\n"); + printf("First time initilizing may cost a few seconds to create cachefile, please wait ...\n"); + + VARP text_embeddings; mModules.resize(3); // load text_encoder model { std::string model_path = modelPath + "/text_encoder.mnn"; mModules[0].reset(Module::load( {"input_ids"}, {"last_hidden_state", "pooler_output"}, model_path.c_str(), runtime_manager_, &module_config)); + + auto outputs = mModules[0]->onForward({mPromptVar}); + text_embeddings = _Convert(outputs[0], NCHW); + display_progress(1, 3); } // load unet model { std::string model_path = modelPath + "/unet.mnn"; mModules[1].reset(Module::load( {"sample", "timestep", "encoder_hidden_states"}, {"out_sample"}, model_path.c_str(), runtime_manager_, &module_config)); + + auto outputs = mModules[1]->onForward({mSampleVar, mTimestepVar, text_embeddings}); + + auto output = _Convert(outputs[0], NCHW); + display_progress(2, 3); } // load vae_decoder model { std::string model_path = modelPath + "/vae_decoder.mnn"; mModules[2].reset(Module::load( {"latent_sample"}, {"sample"}, model_path.c_str(), runtime_manager_, &module_config)); + + auto outputs = mModules[2]->onForward({mLatentVar}); + auto output = _Convert(outputs[0], NCHW); + display_progress(3, 3); } auto exe = ExecutorScope::Current(); @@ -132,16 +159,18 @@ bool Pipeline::load_modules(std::string modelPath) { } VARP Pipeline::text_encoder(const std::vector& ids) { - auto inputs_ids_ = _Const(ids.data(), {2, TEXT_MAX_LEN}, NCHW, halide_type_of()); + AUTOTIME; - auto outputs = mModules[0]->onForward({inputs_ids_}); + memcpy((void *)mPromptVar->writeMap(), ids.data(), 2*mMaxTextLen*sizeof(int)); + + auto outputs = mModules[0]->onForward({mPromptVar}); auto output = _Convert(outputs[0], NCHW); output.fix(VARP::CONSTANT); #ifdef MNN_DUMP_DATA auto xx = output->readMap(); for(int i=0; i<10; i+=2) { - printf("%f %f ", xx[i], xx[i+TEXT_MAX_LEN*768]); + printf("%f %f ", xx[i], xx[i+mMaxTextLen*768]); } printf("\n\n"); #endif @@ -206,16 +235,13 @@ VARP Pipeline::unet(VARP text_embeddings) { } #endif - // VARP latentvar = _Const(initVal.data(), {1, 4, 64, 64}, NCHW); - VARP latentvar = _Input({1, 4, 64, 64}, NCHW, halide_type_of()); - memcpy((void *)latentvar->writeMap(), initVal.data(), 16384*sizeof(float)); + memcpy((void *)mLatentVar->writeMap(), initVal.data(), 16384*sizeof(float)); VARP scalevar = _Input({1}, NCHW, halide_type_of()); auto scaleptr = scalevar->writeMap(); scaleptr[0] = 7.5; - VARP timestepvar = _Input({1}, NCHW, halide_type_of()); auto floatVar = _Input({1}, NCHW, halide_type_of()); auto ptr = floatVar->writeMap(); @@ -223,19 +249,15 @@ VARP Pipeline::unet(VARP text_embeddings) { AUTOTIME; display_progress(i, mTimeSteps.size()); - auto t0 = getTime(); - int timestep = mTimeSteps[i]; ptr[0] = timestep; auto temp = _Cast(floatVar, halide_type_of()); - timestepvar->input(temp); - - VARP samplevar = _Concat({latentvar, latentvar}, 0); - auto outputs = mModules[1]->onForward({samplevar, timestepvar, text_embeddings}); + mTimestepVar->input(temp); + mSampleVar = _Concat({mLatentVar, mLatentVar}, 0); + auto outputs = mModules[1]->onForward({mSampleVar, mTimestepVar, text_embeddings}); auto output = _Convert(outputs[0], NCHW); - auto t1 = getTime(); auto noise_pred = output; @@ -244,42 +266,41 @@ VARP Pipeline::unet(VARP text_embeddings) { auto noise_pred_text = splitvar[1]; noise_pred = scalevar * (noise_pred_text - noise_pred_uncond) + noise_pred_uncond; - auto t2 = getTime(); - latentvar = step_plms(latentvar, noise_pred, i); - auto t3 = getTime(); - MNN_PRINT("Times: %f %f %f ms\n", (t1-t0)/ 1000.0f, (t2-t1)/ 1000.0f, (t3-t2)/ 1000.0f); - // latentvar.fix(VARP::CONSTANT); + mLatentVar = step_plms(mLatentVar, noise_pred, i); + + // mLatentVar.fix(VARP::CONSTANT); #ifdef MNN_DUMP_DATA auto xx = output->readMap(); - auto yy = samplevar->readMap(); + auto yy = mSampleVar->readMap(); auto zz = text_embeddings->readMap(); for(int i=0; i<6; i+=2) { printf("%f %f %f ", xx[i], yy[i], zz[i]); } for(int i=0; i<6; i+=2) { - printf("%f %f %f ", xx[16384+i], yy[16384+i], zz[TEXT_MAX_LEN*768+i]); + printf("%f %f %f ", xx[16384+i], yy[16384+i], zz[mMaxTextLen*768+i]); } printf("\n\n"); #endif } - latentvar.fix(VARP::CONSTANT); + mLatentVar.fix(VARP::CONSTANT); #ifdef MNN_DUMP_DATA - auto xx = latentvar->readMap(); + auto xx = mLatentVar->readMap(); for(int i=0; i<10; i+=2) { printf("%f ", xx[i]); } printf("\n\n"); #endif - return latentvar; + return mLatentVar; } VARP Pipeline::vae_decoder(VARP latent) { mModules[1].reset(); latent = latent * _Const(1 / 0.18215); + AUTOTIME; auto outputs = mModules[2]->onForward({latent}); auto output = _Convert(outputs[0], NCHW); @@ -302,23 +323,25 @@ VARP Pipeline::vae_decoder(VARP latent) { bool Pipeline::run(const std::string& sentence, const std::string& img_name) { std::unique_ptr tok; -// tok.reset(new diffusion::BertTokenizer); - tok.reset(new diffusion::CLIPTokenizer); + if(mModelType == STABLE_DIFFUSION_1_5) { + tok.reset(new diffusion::CLIPTokenizer); + } else if(mModelType == STABLE_DIFFUSION_TAIYI_CHINESE) { + tok.reset(new diffusion::BertTokenizer); + } tok->load(mModelPath); load_modules(mModelPath); - + AUTOTIME; - auto ids = tok->encode(sentence, TEXT_MAX_LEN); + auto ids = tok->encode(sentence, mMaxTextLen); auto text_embeddings = text_encoder(ids); - + auto latent = unet(text_embeddings); + auto image = vae_decoder(latent); bool res = imwrite(img_name, image); if (res) { printf("SUCCESS! write to %s\n", img_name.c_str()); } - // runtime_manager_->updateCache(); - return res; + return true; } - } diff --git a/transformers/diffusion/pipeline.hpp b/transformers/diffusion/pipeline.hpp index b00cec0fb..2d8cc2811 100644 --- a/transformers/diffusion/pipeline.hpp +++ b/transformers/diffusion/pipeline.hpp @@ -11,9 +11,15 @@ using namespace MNN::Express; namespace diffusion { +typedef enum { + STABLE_DIFFUSION_1_5 = 0, + STABLE_DIFFUSION_TAIYI_CHINESE = 1, + DIFFUSION_MODEL_USER +} DiffusionModelType; + class Pipeline { public: - Pipeline(std::string modelPath); + Pipeline(std::string modelPath, DiffusionModelType modelType); ~Pipeline() = default; bool run(const std::string& sentence, const std::string& img_name); private: @@ -27,11 +33,14 @@ class Pipeline { std::vector> mModules; std::string mModelPath; + DiffusionModelType mModelType; + int mMaxTextLen = 77; // step_plms std::vector mTimeSteps; std::vector mAlphas; std::vector mEts; VARP mSample; + VARP mLatentVar, mPromptVar, mTimestepVar, mSampleVar; }; } diff --git a/transformers/diffusion/scheduler/alphas.txt b/transformers/diffusion/scheduler/alphas.txt new file mode 100755 index 000000000..9e1c30b9d --- /dev/null +++ b/transformers/diffusion/scheduler/alphas.txt @@ -0,0 +1,1000 @@ +0.9991 +0.9983 +0.9974 +0.9966 +0.9957 +0.9948 +0.9940 +0.9931 +0.9922 +0.9913 +0.9904 +0.9895 +0.9886 +0.9877 +0.9868 +0.9859 +0.9850 +0.9841 +0.9832 +0.9822 +0.9813 +0.9804 +0.9794 +0.9785 +0.9776 +0.9766 +0.9757 +0.9747 +0.9737 +0.9728 +0.9718 +0.9708 +0.9698 +0.9689 +0.9679 +0.9669 +0.9659 +0.9649 +0.9639 +0.9629 +0.9619 +0.9609 +0.9599 +0.9588 +0.9578 +0.9568 +0.9557 +0.9547 +0.9537 +0.9526 +0.9516 +0.9505 +0.9495 +0.9484 +0.9473 +0.9463 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MNN_ERROR("tokenize load error, vocab.txt not found in %s\n", dictPath.c_str()); return false; } diff --git a/transformers/llm/engine/CMakeLists.txt b/transformers/llm/engine/CMakeLists.txt index 25778d513..767cc272e 100644 --- a/transformers/llm/engine/CMakeLists.txt +++ b/transformers/llm/engine/CMakeLists.txt @@ -9,13 +9,19 @@ if (MSVC) add_library(llm STATIC ${SRCS}) target_link_libraries(llm ${MNN_DEPS}) else() - # compile dynamic so, support Linux/Mac - add_library(llm SHARED ${SRCS}) - set_target_properties(llm PROPERTIES WINDOWS_EXPORT_ALL_SYMBOLS TRUE) - target_link_libraries(llm ${MNN_DEPS}) + if (MNN_SEP_BUILD) + if (MNN_BUILD_SHARED_LIBS) + # compile dynamic so, support Linux/Mac + add_library(llm SHARED ${SRCS}) + set_target_properties(llm PROPERTIES WINDOWS_EXPORT_ALL_SYMBOLS TRUE) + target_link_libraries(llm ${MNN_DEPS}) + else() + add_library(llm STATIC ${SRCS}) + endif() + else() + add_library(llm OBJECT ${SRCS}) + endif() endif() -target_compile_features(llm PRIVATE cxx_std_17) add_executable(llm_demo ${CMAKE_CURRENT_LIST_DIR}/llm_demo.cpp) -target_compile_features(llm_demo PRIVATE cxx_std_17) target_link_libraries(llm_demo llm) \ No newline at end of file diff --git a/transformers/llm/engine/include/llm.hpp b/transformers/llm/engine/include/llm.hpp index 4754010cf..71c3f00fd 100644 --- a/transformers/llm/engine/include/llm.hpp +++ b/transformers/llm/engine/include/llm.hpp @@ -93,32 +93,44 @@ class rapid_json_wrapper { return json_wrapper; } - template - T value(const char* key, const T& defualt_value) const { + int value(const char* key, const int& default_value) const { if (document.HasMember(key)) { const auto& value = document[key]; - if constexpr (std::is_same::value) { - if (value.IsInt()) return value.GetInt(); - } else if constexpr (std::is_same::value || std::is_same::value) { - if (value.IsString()) return value.GetString(); - } else if constexpr (std::is_same::value) { - if (value.IsBool()) return value.GetBool(); - } else if constexpr (std::is_same>::value) { - if (value.IsArray()) { - std::vector result; - for (auto& v : value.GetArray()) { - if (v.IsInt()) { - result.push_back(v.GetInt()); - } + if (value.IsInt()) return value.GetInt(); + } + return default_value; + } + bool value(const char* key, const bool& default_value) const { + if (document.HasMember(key)) { + const auto& value = document[key]; + if (value.IsBool()) return value.GetBool(); + } + return default_value; + } + std::string value(const char* key, const std::string& default_value) const { + if (document.HasMember(key)) { + const auto& value = document[key]; + if (value.IsString()) return value.GetString(); + } + return default_value; + } + std::vector value(const char* key, const std::vector& default_value) const { + if (document.HasMember(key)) { + const auto& value = document[key]; + if (value.IsArray()) { + std::vector result; + for (auto& v : value.GetArray()) { + if (v.IsInt()) { + result.push_back(v.GetInt()); } - return result; } + return result; } } - return defualt_value; + return default_value; } - std::string value(const char key[], const char defualt_value[]) const { - return value(key, std::string(defualt_value)); + std::string value(const char key[], const char default_value[]) const { + return value(key, std::string(default_value)); } }; @@ -251,6 +263,10 @@ class LlmConfig { return llm_config_.value("attention_mask", "int"); } + std::string chat_template() const { + return llm_config_.value("chat_template", ""); + } + std::string prompt_template() const { return llm_config_.value("prompt_template", ""); } @@ -258,6 +274,7 @@ class LlmConfig { }; class MNN_PUBLIC Llm { + using PromptItem = std::pair; // public: Llm(std::shared_ptr config) : config_(config) {} virtual ~Llm(); @@ -267,8 +284,10 @@ class MNN_PUBLIC Llm { virtual void load(); VARP forward(const std::vector& input_ids); int sample(VARP logits, const std::vector& pre_ids); - std::string apply_chat_template(const std::string& input_str) const; - std::string response(const std::string& input_str, std::ostream* os = &std::cout, const char* end_with = nullptr); + std::string apply_prompt_template(const std::string& user_content) const; + std::string apply_chat_template(const std::vector& chat_prompts) const; + std::string response(const std::string& user_content, std::ostream* os = &std::cout, const char* end_with = nullptr); + std::string response(const std::vector& chat_prompts, std::ostream* os = &std::cout, const char* end_with = nullptr); void generate_init(); std::string generate(const std::vector& input_ids, std::ostream* os, const char* end_with); std::vector generate(const std::vector& input_ids, int max_new_tokens = -1); diff --git a/transformers/llm/engine/include/tokenizer.hpp b/transformers/llm/engine/include/tokenizer.hpp index 16d10861d..e30cd980e 100644 --- a/transformers/llm/engine/include/tokenizer.hpp +++ b/transformers/llm/engine/include/tokenizer.hpp @@ -13,7 +13,54 @@ #include #include #include -#include +// #include +#include + +// std::string_view impl in c++11 start +class string_view_ { +public: + string_view_() : data_(nullptr), size_(0) {} + string_view_(const char* data) : data_(data), size_(std::strlen(data)) {} + string_view_(const char* data, std::size_t size) : data_(data), size_(size) {} + string_view_(const std::string& str) : data_(str.data()), size_(str.size()) {} + constexpr string_view_(const string_view_&) noexcept = default; + string_view_& operator=(const string_view_&) noexcept = default; + const char& operator[](size_t pos) const { return data_[pos]; } + constexpr const char* data() const noexcept { return data_; } + constexpr std::size_t size() const noexcept { return size_; } + constexpr bool empty() const { return size_ == 0; } + std::string to_string() const { return std::string(data_, size_); } + bool operator==(const string_view_& other) const noexcept { + return size_ == other.size_ && strncmp(data_, other.data_, size_) == 0; + } + void remove_prefix(size_t n) { + if (n < size_) { + data_ += n; + size_ -= n; + } else { + data_ = ""; + size_ = 0; + } + } +private: + const char* data_; + std::size_t size_ = 0; +}; + +namespace std { + template<> + class hash { + public: + size_t operator()(const string_view_& sv) const { + size_t result = 0; + for (size_t i = 0; i < sv.size(); ++i) { + result = (result * 31) + static_cast(sv[i]); + } + return result; + } + }; +} +// std::string_view impl in c++11 end class Tokenizer { public: @@ -28,6 +75,7 @@ class Tokenizer { virtual ~Tokenizer() = default; static Tokenizer* createTokenizer(const std::string& filename); bool is_stop(int token); + bool is_special(int token); std::vector encode(const std::string& str); virtual std::string decode(int id) = 0; protected: @@ -65,8 +113,10 @@ class Sentencepiece : public Tokenizer { std::string piece; float score; PieceType type = PieceType::NORMAL; + SentencePiece() {} + SentencePiece(const std::string& p, float s, PieceType t) : piece(p), score(s), type(t) {} }; - using EncodeResult = std::vector>; + using EncodeResult = std::vector>; private: // model train type ModelType type_ = BPE; @@ -86,7 +136,7 @@ class Sentencepiece : public Tokenizer { bool is_control(int id) const; int piece_to_id(const std::string& w) const; std::string byte_to_piece(unsigned char c) const; - EncodeResult bpe_encode(std::string_view str, float alpha = 0.f); + EncodeResult bpe_encode(string_view_ str, float alpha = 0.f); }; class Tiktoken : public Tokenizer { diff --git a/transformers/llm/engine/llm_demo.cpp b/transformers/llm/engine/llm_demo.cpp index 3c6512661..4edc7731d 100644 --- a/transformers/llm/engine/llm_demo.cpp +++ b/transformers/llm/engine/llm_demo.cpp @@ -187,6 +187,7 @@ int main(int argc, const char* argv[]) { } if (argc < 3) { llm->chat(); + return 0; } std::string prompt_file = argv[2]; return eval(llm.get(), prompt_file); diff --git a/transformers/llm/engine/src/llm.cpp b/transformers/llm/engine/src/llm.cpp index 86ff80596..3838d8538 100644 --- a/transformers/llm/engine/src/llm.cpp +++ b/transformers/llm/engine/src/llm.cpp @@ -9,6 +9,7 @@ #include #include #include +#include #include #include @@ -180,17 +181,18 @@ VARP Llm::forward(const std::vector& input_ids) { } int Llm::sample(VARP logits, const std::vector& pre_ids) { + std::unordered_set ids_set(pre_ids.begin(), pre_ids.end()); auto scores = (float*)(logits->readMap()); auto size = logits->getInfo()->size; - float max_score = 0; - int token_id = 0; // repetition penalty const float repetition_penalty = 1.1; - for (auto id : pre_ids) { + for (auto id : ids_set) { float score = scores[id]; scores[id] = score < 0 ? score * repetition_penalty : score / repetition_penalty; } // argmax + float max_score = 0; + int token_id = 0; for (int i = 0; i < size; i++) { float score = scores[i]; if (score > max_score) { @@ -201,31 +203,60 @@ int Llm::sample(VARP logits, const std::vector& pre_ids) { return token_id; } -std::string Llm::apply_chat_template(const std::string& input_str) const { - auto prompt = config_->prompt_template(); - if (prompt.empty()) return input_str; +static std::string apply_template(std::string prompt_template, const std::string& content, const std::string& role = "") { + if (prompt_template.empty()) return content; + if (!role.empty()) { + const std::string placeholder = "%r"; + size_t start_pos = prompt_template.find(placeholder); + if (start_pos == std::string::npos) return content; + prompt_template.replace(start_pos, placeholder.length(), role); + } const std::string placeholder = "%s"; - size_t start_pos = prompt.find(placeholder); - if (start_pos == std::string::npos) return input_str; - prompt.replace(start_pos, placeholder.length(), input_str); - return prompt; + size_t start_pos = prompt_template.find(placeholder); + if (start_pos == std::string::npos) return content; + prompt_template.replace(start_pos, placeholder.length(), content); + return prompt_template; +} + +std::string Llm::apply_prompt_template(const std::string& user_content) const { + auto chat_prompt = config_->prompt_template(); + return apply_template(chat_prompt, user_content); +} + +std::string Llm::apply_chat_template(const std::vector& chat_prompts) const { + auto chat_template = config_->chat_template(); + std::string prompt_result; + auto iter = chat_prompts.begin(); + for (; iter != chat_prompts.end() - 1; ++iter) { + prompt_result += apply_template(chat_template, iter->second, iter->first); + } + if (iter->first == "user") { + prompt_result += apply_prompt_template(iter->second); + } else { + prompt_result += apply_template(chat_template, iter->second, iter->first); + } + return prompt_result; } void Llm::chat() { + std::vector history; + history.push_back(std::make_pair("system", "You are a helpful assistant.")); while (true) { std::cout << "\nQ: "; - std::string input_str; - std::cin >> input_str; - if (input_str == "/exit") { + std::string user_str; + std::cin >> user_str; + if (user_str == "/exit") { break; } - if (input_str == "/reset") { - // reset(); + if (user_str == "/reset") { + history.resize(1); std::cout << "\nA: reset done." << std::endl; continue; } std::cout << "\nA: " << std::flush; - response(input_str); + history.emplace_back(std::make_pair("user", user_str)); + auto assistant_str = response(history); + history.emplace_back(std::make_pair("assistant", assistant_str)); std::cout << std::endl; } } @@ -316,18 +347,28 @@ std::string Llm::generate(const std::vector& input_ids, std::ostream* os, c return output_str; } -std::vector Llm::tokenizer(const std::string& query) { - auto prompt = apply_chat_template(query); +std::vector Llm::tokenizer(const std::string& user_content) { + auto prompt = apply_prompt_template(user_content); auto input_ids = tokenizer_->encode(prompt); return input_ids; } -std::string Llm::response(const std::string& query, std::ostream* os, const char* end_with) { +std::string Llm::response(const std::string& user_content, std::ostream* os, const char* end_with) { generate_init(); if (!end_with) { end_with = "\n"; } - auto input_ids = tokenizer(query); + auto input_ids = tokenizer(user_content); return generate(input_ids, os, end_with); } + +std::string Llm::response(const std::vector& chat_prompts, std::ostream* os, const char* end_with) { + if (chat_prompts.empty()) { return ""; } + generate_init(); + if (!end_with) { end_with = "\n"; } + auto prompt = apply_chat_template(chat_prompts); + auto input_ids = tokenizer_->encode(prompt); + return generate(input_ids, os, end_with); +} + Llm::~Llm() { #if DEBUG_MODE==1 if (nullptr != gTimeTraceInfo) { @@ -522,7 +563,7 @@ std::vector Lvlm::url_encode(const std::string& url) { } std::vector Lvlm::tokenizer(const std::string& query) { - auto prompt = apply_chat_template(query); + auto prompt = apply_prompt_template(query); // split query std::regex img_regex("(.*?)"); std::string::const_iterator searchStart(prompt.cbegin()); @@ -666,7 +707,7 @@ std::vector Embedding::tokenizer(const std::string& query) { if (query.size() <= 256) { prompt = "为这个句子生成表示以用于检索相关文章：" + query; } - prompt = apply_chat_template(prompt); + prompt = apply_prompt_template(prompt); auto ids = tokenizer_->encode(prompt); return ids; } diff --git a/transformers/llm/engine/src/tokenizer.cpp b/transformers/llm/engine/src/tokenizer.cpp index d6f6490c8..f0350adc9 100644 --- a/transformers/llm/engine/src/tokenizer.cpp +++ b/transformers/llm/engine/src/tokenizer.cpp @@ -128,6 +128,10 @@ bool Tokenizer::is_stop(int token) { return std::find(stop_tokens_.begin(), stop_tokens_.end(), token) != stop_tokens_.end(); } +bool Tokenizer::is_special(int token) { + return std::find(special_tokens_.begin(), special_tokens_.end(), token) != special_tokens_.end(); +} + void Tokenizer::load_special(std::ifstream& tok_file) { std::string line; std::getline(tok_file, line); @@ -201,7 +205,7 @@ bool Sentencepiece::load_vocab(std::ifstream& tok_file) { line_str >> token >> score >> type; token = base64_decode(token); auto piece_type = static_cast(type); - SentencePiece piece {token, score, piece_type}; + SentencePiece piece = {token, score, piece_type}; sentence_pieces_[index] = std::move(piece); if (piece_type == PieceType::NORMAL) { pieces_.insert({token, index}); @@ -236,7 +240,7 @@ std::string Sentencepiece::byte_to_piece(unsigned char c) const { } // ref: https://github.com/google/sentencepiece/blob/master/src/bpe_model.cc -Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalized, float alpha) { +Sentencepiece::EncodeResult Sentencepiece::bpe_encode(string_view_ normalized, float alpha) { // util class begin struct SymbolPair { int left; // left index of this pair @@ -256,7 +260,7 @@ Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalize int prev; // prev index of this symbol. -1 for BOS. int next; // next index of tihs symbol. -1 for EOS. bool freeze = false; // this symbol is never be merged. - std::string_view piece; + string_view_ piece; }; // util class end @@ -265,7 +269,7 @@ Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalize std::vector symbols; symbols.reserve(normalized.size()); // Reverse merge rules. key: merged symbol, value: pair of original symbols. - std::unordered_map> rev_merge; + std::unordered_map> rev_merge; // SymbolPair holder. std::vector> symbol_pair_holder; // Lookup new symbol pair at [left, right] and inserts it to agenda. @@ -273,8 +277,8 @@ Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalize if (left == -1 || right == -1 || symbols[left].freeze || symbols[right].freeze) { return; } - const std::string_view piece(symbols[left].piece.data(), symbols[left].piece.size() + symbols[right].piece.size()); - std::string piece_str(piece); + const string_view_ piece(symbols[left].piece.data(), symbols[left].piece.size() + symbols[right].piece.size()); + std::string piece_str(piece.to_string()); const auto it = pieces_.find(piece_str); if (it == pieces_.end()) { return; @@ -298,7 +302,7 @@ Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalize Symbol s; // const int mblen = matcher_->PrefixMatch(normalized, &s.freeze); int mblen = std::min(normalized.size(), one_char_len(normalized.data())); - s.piece = std::string_view(normalized.data(), mblen); + s.piece = string_view_(normalized.data(), mblen); s.prev = index == 0 ? -1 : index - 1; normalized.remove_prefix(mblen); s.next = normalized.empty() ? -1 : index + 1; @@ -338,7 +342,7 @@ Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalize if (skip_merge()) continue; // Replaces symbols with `top` rule. - symbols[top->left].piece = std::string_view( + symbols[top->left].piece = string_view_( symbols[top->left].piece.data(), symbols[top->left].piece.size() + symbols[top->right].piece.size()); @@ -347,16 +351,16 @@ Sentencepiece::EncodeResult Sentencepiece::bpe_encode(std::string_view normalize if (symbols[top->right].next >= 0) { symbols[symbols[top->right].next].prev = top->left; } - symbols[top->right].piece = std::string_view(""); + symbols[top->right].piece = string_view_(""); // Adds new symbol pairs which are newly added after symbol replacement. MaybeAddNewSymbolPair(symbols[top->left].prev, top->left); MaybeAddNewSymbolPair(top->left, symbols[top->left].next); } - std::function resegment; - resegment = [this, &resegment, &rev_merge](std::string_view w, EncodeResult *output) -> void { - std::string w_str(w); + std::function resegment; + resegment = [this, &resegment, &rev_merge](string_view_ w, EncodeResult *output) -> void { + std::string w_str(w.to_string()); const int id = piece_to_id(w_str); // std::cout << "piece: " << w << ", id = " << id << std::endl; if (id == -1 || !is_unused(id)) { @@ -385,7 +389,7 @@ void Sentencepiece::encode(const std::string& str, std::vector& ids) { auto result = bpe_encode(str); size_t consumed = 0; for (const auto &p : result) { - const std::string_view w = p.first; // piece + const string_view_ w = p.first; // piece const int id = p.second; // id const bool is_unk = (id == unk_id_); if (is_unk && byte_fall_back_) { diff --git a/transformers/llm/eval/evaluate_chat_ceval.py b/transformers/llm/eval/evaluate_chat_ceval.py new file mode 100644 index 000000000..50d47f35e --- /dev/null +++ b/transformers/llm/eval/evaluate_chat_ceval.py @@ -0,0 +1,508 @@ +import os +import argparse +import re +import torch +import pandas as pd +from thefuzz import process +from tqdm import tqdm +from transformers import AutoTokenizer +import MNN.llm as mnnllm + +''' +export HF_ENDPOINT=https://hf-mirror.com +wget https://huggingface.co/datasets/ceval/ceval-exam/resolve/main/ceval-exam.zip +mkdir data/ceval +mv ceval-exam.zip data/ceval +cd data/ceval; unzip ceval-exam.zip +cd ../../ + +pip install thefuzz +python eval/evaluate_chat_ceval.py -d data/ceval +''' + +def load_models_tokenizer(args): + tokenizer = AutoTokenizer.from_pretrained( + args.checkpoint_path, trust_remote_code=True + ) + model = mnnllm.create(args.mnn_path) + model.load() + return model, tokenizer + +def process_before_extraction(gen, question, choice_dict): + # Example Prompt: + # 关于传输层的面向连接服务的特性是____。 + # A. 既不保证可靠，也不保证按序交付 + # B. 不保证可靠，但保证按序交付 + # C. 保证可靠，但不保证按序交付 + # D. 既保证可靠，也保证按序交付 + # Example Model Output： + # 关于传输层的面向连接服务的特性是既保证可靠，也保证按序交付 + # Processed Output: + # 答案是D + + question_split = question.rstrip("。").split("。")[-1].split("_") + + # replacing the question + if len(question_split[0].strip()) > 4: + gen = gen.replace(question_split[0], "答案是") + if len(question_split[-1].strip()) > 4: + gen = gen.replace(question_split[-1], "") + + # replace the choice by letter in the generated sentence + # from longest one to shortest one + for key, val in sorted(choice_dict.items(), key=lambda x: len(x[1]), reverse=True): + gen = gen.replace(val.rstrip("。"), key) + + return gen + + +def count_substr(gen, pattern): + return len(re.findall(pattern, gen)) + + +def extract_choice(gen, prompt, choice_list): + # 答案是A | 选项是A | 应该选A选项 + res = re.search( + r"(?:(?:选|选择|选定)[：:]?\s*|(?:(?:答案|选项)(?![^ABCD]{0,10}?(?:不|非)[^ABCD]{0,10}?(?:是|选|为|：|:|】))[^ABCD]{0,10}?(?:是|选|为|：|:|】))[^ABCD]{0,10}?)(A|B|C|D)(?:选项)?(?:\)|。|\.|，|,|．|、|A|B|C|D|$|：|:|\)|）)", + gen, + ) + + # A选项正确 | A选项符合题意 + if res is None: + res = re.search( + r"(A|B|C|D)(?:选?项)?(?![^ABCD]{0,4}?(?:不|非)[^ABCD]{0,4}?(?:正确|对[的，。：]|符合))[^ABCD]{0,4}?(?:正确|对[的，。：]|符合)", + gen, + ) + + # 直接输出 A + if res is None: + res = re.search(r"^[\(（]?(A|B|C|D)(?:。|\)|）|\.|，|,|．|：|:|$)", gen) + + # 获取第一个出现的字母 + if res is None: + res = re.search(r"(? 0: + print("Hard acc:%.2f " % (hard_acc_sum / hard_cnt)) + print("AVERAGE acc:%.2f " % (acc_sum / cnt)) + + +''' +TASK_NAME_MAPPING = { + "computer_network": ["Computer Network", "\u8ba1\u7b97\u673a\u7f51\u7edc", "STEM"], + "operating_system": ["Operating System", "\u64cd\u4f5c\u7cfb\u7edf", "STEM"], + "computer_architecture": [ + "Computer Architecture", + "\u8ba1\u7b97\u673a\u7ec4\u6210", + "STEM", + ], + "college_programming": ["College Programming", "\u5927\u5b66\u7f16\u7a0b", "STEM"], + "college_physics": ["College Physics", "\u5927\u5b66\u7269\u7406", "STEM"], + "college_chemistry": ["College Chemistry", "\u5927\u5b66\u5316\u5b66", "STEM"], + "advanced_mathematics": [ + "Advanced Mathematics", + "\u9ad8\u7b49\u6570\u5b66", + "STEM", + ], + "probability_and_statistics": [ + "Probability and Statistics", + "\u6982\u7387\u7edf\u8ba1", + "STEM", + ], + "discrete_mathematics": [ + "Discrete Mathematics", + "\u79bb\u6563\u6570\u5b66", + "STEM", + ], + "electrical_engineer": [ + "Electrical Engineer", + "\u6ce8\u518c\u7535\u6c14\u5de5\u7a0b\u5e08", + "STEM", + ], + "metrology_engineer": [ + "Metrology Engineer", + "\u6ce8\u518c\u8ba1\u91cf\u5e08", + "STEM", + ], + "high_school_mathematics": [ + "High School Mathematics", + "\u9ad8\u4e2d\u6570\u5b66", + "STEM", + ], + "high_school_physics": ["High School Physics", "\u9ad8\u4e2d\u7269\u7406", "STEM"], + "high_school_chemistry": [ + "High School Chemistry", + "\u9ad8\u4e2d\u5316\u5b66", + "STEM", + ], + "high_school_biology": ["High School Biology", "\u9ad8\u4e2d\u751f\u7269", "STEM"], + "middle_school_mathematics": [ + "Middle School Mathematics", + "\u521d\u4e2d\u6570\u5b66", + "STEM", + ], + "middle_school_biology": [ + "Middle School Biology", + "\u521d\u4e2d\u751f\u7269", + "STEM", + ], + "middle_school_physics": [ + "Middle School Physics", + "\u521d\u4e2d\u7269\u7406", + "STEM", + ], + "middle_school_chemistry": [ + "Middle School Chemistry", + "\u521d\u4e2d\u5316\u5b66", + "STEM", + ], + "veterinary_medicine": ["Veterinary Medicine", "\u517d\u533b\u5b66", "STEM"], + "college_economics": [ + "College Economics", + "\u5927\u5b66\u7ecf\u6d4e\u5b66", + "Social Science", + ], + "business_administration": [ + "Business Administration", + "\u5de5\u5546\u7ba1\u7406", + "Social Science", + ], + "marxism": [ + "Marxism", + "\u9a6c\u514b\u601d\u4e3b\u4e49\u57fa\u672c\u539f\u7406", + "Social Science", + ], + "mao_zedong_thought": [ + "Mao Zedong Thought", + "\u6bdb\u6cfd\u4e1c\u601d\u60f3\u548c\u4e2d\u56fd\u7279\u8272\u793e\u4f1a\u4e3b\u4e49\u7406\u8bba\u4f53\u7cfb\u6982\u8bba", + "Social Science", + ], + "education_science": ["Education Science", "\u6559\u80b2\u5b66", "Social Science"], + "teacher_qualification": [ + "Teacher Qualification", + "\u6559\u5e08\u8d44\u683c", + "Social Science", + ], + "high_school_politics": [ + "High School Politics", + "\u9ad8\u4e2d\u653f\u6cbb", + "Social Science", + ], + "high_school_geography": [ + "High School Geography", + "\u9ad8\u4e2d\u5730\u7406", + "Social Science", + ], + "middle_school_politics": [ + "Middle School Politics", + "\u521d\u4e2d\u653f\u6cbb", + "Social Science", + ], + "middle_school_geography": [ + "Middle School Geography", + "\u521d\u4e2d\u5730\u7406", + "Social Science", + ], + "modern_chinese_history": [ + "Modern Chinese History", + "\u8fd1\u4ee3\u53f2\u7eb2\u8981", + "Humanities", + ], + "ideological_and_moral_cultivation": [ + "Ideological and Moral Cultivation", + "\u601d\u60f3\u9053\u5fb7\u4fee\u517b\u4e0e\u6cd5\u5f8b\u57fa\u7840", + "Humanities", + ], + "logic": ["Logic", "\u903b\u8f91\u5b66", "Humanities"], + "law": ["Law", "\u6cd5\u5b66", "Humanities"], + "chinese_language_and_literature": [ + "Chinese Language and Literature", + "\u4e2d\u56fd\u8bed\u8a00\u6587\u5b66", + "Humanities", + ], + "art_studies": ["Art Studies", "\u827a\u672f\u5b66", "Humanities"], + "professional_tour_guide": [ + "Professional Tour Guide", + "\u5bfc\u6e38\u8d44\u683c", + "Humanities", + ], + "legal_professional": [ + "Legal Professional", + "\u6cd5\u5f8b\u804c\u4e1a\u8d44\u683c", + "Humanities", + ], + "high_school_chinese": [ + "High School Chinese", + "\u9ad8\u4e2d\u8bed\u6587", + "Humanities", + ], + "high_school_history": [ + "High School History", + "\u9ad8\u4e2d\u5386\u53f2", + "Humanities", + ], + "middle_school_history": [ + "Middle School History", + "\u521d\u4e2d\u5386\u53f2", + "Humanities", + ], + "civil_servant": ["Civil Servant", "\u516c\u52a1\u5458", "Other"], + "sports_science": ["Sports Science", "\u4f53\u80b2\u5b66", "Other"], + "plant_protection": ["Plant Protection", "\u690d\u7269\u4fdd\u62a4", "Other"], + "basic_medicine": ["Basic Medicine", "\u57fa\u7840\u533b\u5b66", "Other"], + "clinical_medicine": ["Clinical Medicine", "\u4e34\u5e8a\u533b\u5b66", "Other"], + "urban_and_rural_planner": [ + "Urban and Rural Planner", + "\u6ce8\u518c\u57ce\u4e61\u89c4\u5212\u5e08", + "Other", + ], + "accountant": ["Accountant", "\u6ce8\u518c\u4f1a\u8ba1\u5e08", "Other"], + "fire_engineer": [ + "Fire Engineer", + "\u6ce8\u518c\u6d88\u9632\u5de5\u7a0b\u5e08", + "Other", + ], + "environmental_impact_assessment_engineer": [ + "Environmental Impact Assessment Engineer", + "\u73af\u5883\u5f71\u54cd\u8bc4\u4ef7\u5de5\u7a0b\u5e08", + "Other", + ], + "tax_accountant": ["Tax Accountant", "\u7a0e\u52a1\u5e08", "Other"], + "physician": ["Physician", "\u533b\u5e08\u8d44\u683c", "Other"], +} +''' +TASK_NAME_MAPPING = { + "teacher_qualification": [ + "Teacher Qualification", + "\u6559\u5e08\u8d44\u683c", + "Social Science", + ], + "marxism": [ + "Marxism", + "\u9a6c\u514b\u601d\u4e3b\u4e49\u57fa\u672c\u539f\u7406", + "Social Science", + ], + "middle_school_politics": [ + "Middle School Politics", + "\u521d\u4e2d\u653f\u6cbb", + "Social Science", + ], + "middle_school_history": [ + "Middle School History", + "\u521d\u4e2d\u5386\u53f2", + "Humanities", + ], + "middle_school_chemistry": [ + "Middle School Chemistry", + "\u521d\u4e2d\u5316\u5b66", + "STEM", + ], + "modern_chinese_history": [ + "Modern Chinese History", + "\u8fd1\u4ee3\u53f2\u7eb2\u8981", + "Humanities", + ], +} +hard_list = [ + "advanced_mathematics", + "discrete_mathematics", + "probability_and_statistics", + "college_physics", + "college_chemistry", + "high_school_mathematics", + "high_school_physics", + "high_school_chemistry", +] +choices = ["A", "B", "C", "D"] + + +def main(args): + print("loading model weights") + if args.checkpoint_path: + model, tokenizer = load_models_tokenizer(args) + else: + model, tokenizer = None, None + print("model loaded") + dev_result = {} + for subject_name in tqdm(TASK_NAME_MAPPING.keys()): + val_file_path = os.path.join( + args.eval_data_path, "val", f"{subject_name}_val.csv" + ) + val_df = pd.read_csv(val_file_path) + + score = eval_subject( + model, + tokenizer, + subject_name, + val_df, + save_result_dir="outs_chat/ceval_eval_result", + overwrite=args.overwrite, + ) + dev_result[subject_name] = score + print(dev_result) + cal_ceval(dev_result) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Test HF checkpoint.") + parser.add_argument( + "-c", + "--checkpoint-path", + type=str, + help="Checkpoint path", + default="/Users/wangzhaode/Qwen1_5-1_8B-Chat", + ) + parser.add_argument( + "-m", + "--mnn-path", + type=str, + help="mnn model path", + default="/home/yanxing/data/qwen-1.8b-int4/config.json", + ) + + # Provide extra arguments required for tasks + group = parser.add_argument_group(title="Evaluation options") + group.add_argument( + "-d", "--eval_data_path", type=str, required=True, help="Path to eval data" + ) + group.add_argument( + "--debug", action="store_true", default=False, help="Print infos." + ) + group.add_argument( + "--overwrite", + action="store_true", + default=False, + help="Overwrite existed results", + ) + + args = parser.parse_args() + + main(args)