Updated to version 2.2.0.

Dockerfile

@@ -15,12 +15,12 @@ RUN DEBIAN_FRONTEND=noninteractive apt-get install -y python3-pip
 RUN locale-gen en_US.UTF-8
 RUN pip3 install --upgrade pip
 RUN pip3 install decorator attrs scipy numpy==1.23.5 pytest
-RUN pip3 install torch==1.8.0 torchvision==0.9.0 tensorflow tflite psutil
+RUN pip3 install torch==1.8.0 torchvision==0.9.0 tensorflow tflite psutil typing-extensions==4.5.0
 
 # Install onnxruntime
-RUN wget https://github.com/microsoft/onnxruntime/releases/download/v1.8.1/onnxruntime-linux-x64-1.8.1.tgz -O /tmp/onnxruntime.tar.gz \
+RUN wget https://github.com/microsoft/onnxruntime/releases/download/v1.16.1/onnxruntime-linux-x64-1.16.1.tgz -O /tmp/onnxruntime.tar.gz \
     && tar -xvzf /tmp/onnxruntime.tar.gz -C /tmp/ \
-    && mv /tmp/onnxruntime-linux-x64-1.8.1/ /opt/
+    && mv /tmp/onnxruntime-linux-x64-1.16.1/ /opt/
 
 # Install SDK
 COPY ./poky*.sh /opt

DockerfileV2H

@@ -35,14 +35,14 @@ RUN cd /opt && yes "" | ./poky*.sh
 RUN rm /opt/poky*.sh
 
 # Install DRP-AI Translator
-COPY ./DRP-AI_Translator_i8-v*-Linux-x86_64-Install /opt
-RUN chmod a+x /opt/DRP-AI_Translator_i8-v*-Linux-x86_64-Install
-RUN cd /opt && yes | ./DRP-AI_Translator_i8-v*-Linux-x86_64-Install
-RUN rm /opt/DRP-AI_Translator_i8-v*-Linux-x86_64-Install
+COPY ./DRP-AI_Translator_i8-*-Linux-x86_64-Install  /opt
+RUN chmod a+x /opt/DRP-AI_Translator_i8-*-Linux-x86_64-Install
+RUN cd /opt && yes | ./DRP-AI_Translator_i8-*-Linux-x86_64-Install
+RUN rm /opt/DRP-AI_Translator_i8-*-Linux-x86_64-Install
 
 # Clone repository
 ENV TVM_ROOT="/drp-ai_tvm"
-RUN git clone --recursive -b v2.1.0 https://github.com/renesas-rz/rzv_drp-ai_tvm.git ${TVM_ROOT}
+RUN git clone --recursive https://github.com/renesas-rz/rzv_drp-ai_tvm.git ${TVM_ROOT}
 
 # Set environment variables
 ENV TVM_ROOT=${TVM_ROOT}

README.md

@@ -15,15 +15,16 @@ Contributors Licensed under an Apache-2.0 license.
 - Renesas RZ/V2L Evaluation Board Kit ([How to get](https://www.renesas.com/document/gde/rzv2l-contents-guide))
 - Renesas RZ/V2M Evaluation Board Kit ([How to get](https://www.renesas.com/document/gde/rzv2m-contents-guide))
 - Renesas RZ/V2MA Evaluation Board Kit ([How to get](https://www.renesas.com/document/gde/rzv2ma-contents-guide))
+- Renesas RZ/V2H Evaluation Board Kit
 
 ## Introduction
 ### Overview   
 This compiler stack is an extension of the DRP-AI Translator to the TVM backend. CPU and DRP-AI can work together for the inference processing of the AI models.  
 
-<img src=./img/tool_stack.png width=350>   
-
+<img src=./img/tool_stack.png width=350>
 
 ### File Configuration
+
 | Directory | Details |
 |:---|:---|
 |tutorials |Sample compile script|
@@ -32,15 +33,15 @@ This compiler stack is an extension of the DRP-AI Translator to the TVM backend.
 |obj |Pre-build runtime binaries|
 |docs |Documents, i.e., Model list and API list|
 |img |Image files used in this document|
-|tvm | TVM repository from github |
-|3rdparty | 3rd party tools |   
+|tvm | TVM repository from GitHub |
+|3rdparty | 3rd party tools |
 |how-to |Sample to solve specific problems, i.e., How to run validation between x86 and DRP-AI|
+|pruning | Sample scripts to prune the models with DRP-AI Extension Package  |
 
 
 ## Installation
-- [Installing DRP-AI TVM](./setup/README.md#installing-drp-ai-tvm1)
-- [Installing DRP-AI TVM for RZ/V2H](./setup/SetupV2H.md#hogehoge)
-- [Installing DRP-AI TVM with Docker](./setup/README.md#installing-drp-ai-tvm1-with-docker)
+- [Installing DRP-AI TVM (RZ/V2L, RZ/V2M, RZ/V2MA)](./setup/README.md)
+- [Installing DRP-AI TVM (RZ/V2H)](./setup/SetupV2H.md)
 
 ## Deploy AI models on DRP-AI
 ### Video
@@ -56,19 +57,31 @@ SDK generated from RZ/V Linux Package and DRP-AI Support Package is required to
 After compiled the model, you need to copy the file to the target board (Deploy).  
 You also need to copy the C++ inference application and DRP-AI TVM[^1] Runtime Library to run the AI model inference.  
 
-<img src=./img/deploy_flow.png width=500>
+| RZ/V2L, RZ/V2M, RZ/V2MA |
+|:---|
+|<img src=./img/deploy_flow.png width=500>|
+
+| RZ/V2H |
+|:---|
+|<img src=./img/deploy_flow_V2H.png width=500>|
+
 
 Following pages show the example to compile the ResNet18 model and run it on the target board.  
 
+### [Option] Prune the model with DRP-AI Extension Package
+- [What is Pruning and Quantization?](./pruning/README.md)
+- [Installing DRP-AI Extention Package](./pruning/setup/README.md)
+- [Pruning and retraining by DRP-AI Extension Package](./pruning/how-to/torchvision_resnet50/README.md)
+
 ### Compile model with DRP-AI TVM[^1]  
 
-- [Compiling model for DRP-AI TVM](./tutorials)
-- [Compiling model for DRP-AI TVM(RZ/V2H)](./tutorials/tutorial_RZV2H.md)
+- [Compiling model for DRP-AI TVM (RZ/V2L, RZ/V2M, RZ/V2MA)](./tutorials)
+- [Compiling model for DRP-AI TVM (RZ/V2H)](./tutorials/tutorial_RZV2H.md)
 
 ### Run inference on board  
 
-- [Application Example for DRP-AI TVM](./apps)
-- [Application Example for DRP-AI TVM(RZ/V2H)](./apps/build_appV2H.md)
+- [Application Example for DRP-AI TVM (RZ/V2L, RZ/V2M, RZ/V2MA)](./apps)
+- [Application Example for DRP-AI TVM (RZ/V2H)](./apps/build_appV2H.md)
 
 ## Sample Application  
 To find more AI examples, please see [How-to](./how-to) page.  

apps/CMakeLists.txt

@@ -7,16 +7,13 @@ include_directories(${TVM_ROOT}/include)
 include_directories(${TVM_ROOT}/3rdparty/dlpack/include)
 include_directories(${TVM_ROOT}/3rdparty/dmlc-core/include)
 include_directories(${TVM_ROOT}/3rdparty/compiler-rt)
-include_directories($ENV{SDK}/sysroots/aarch64-poky-linux/usr/include/opencv4)
+#include_directories($ENV{SDK}/sysroots/aarch64-poky-linux/usr/include/opencv4)
 
 set(TVM_RUNTIME_LIB ${TVM_ROOT}/build_runtime/libtvm_runtime.so)
-if(OCV)
-  set(SRC tutorial_app.cpp MeraDrpRuntimeWrapper.cpp PreRuntimeOcv.cpp)
-  find_package(OpenCV REQUIRED)
-elseif(V2H)
+if(V2H)
   set(SRC tutorial_app.cpp MeraDrpRuntimeWrapper.cpp PreRuntimeV2H.cpp)
 else()
-  set(SRC tutorial_app.cpp MeraDrpRuntimeWrapper.cpp PreRuntime.cpp)
+  set(SRC tutorial_app_v2ml.cpp MeraDrpRuntimeWrapper.cpp PreRuntime.cpp)
 endif()
 
 

apps/MeraDrpRuntimeWrapper.cpp

@@ -136,6 +136,10 @@ void MeraDrpRuntimeWrapper::Run() {
     mod.GetFunction("run")();
 }
 
+void MeraDrpRuntimeWrapper::Run(int freq_index) {
+    mod.GetFunction("run")(freq_index);
+}
+
 void MeraDrpRuntimeWrapper::ProfileRun(const std::string& profile_table, const std::string& profile_csv) {
     tvm::runtime::PackedFunc profile = mod.GetFunction("profile");
     tvm::runtime::Array<tvm::runtime::profiling::MetricCollector> collectors;
@@ -152,6 +156,22 @@ void MeraDrpRuntimeWrapper::ProfileRun(const std::string& profile_table, const s
     ofs_csv.close();
 }
 
+void MeraDrpRuntimeWrapper::ProfileRun(const std::string& profile_table, const std::string& profile_csv, int freq_index) {
+    tvm::runtime::PackedFunc profile = mod.GetFunction("profile");
+    tvm::runtime::Array<tvm::runtime::profiling::MetricCollector> collectors;
+    tvm::runtime::profiling::Report report = profile(collectors, freq_index);
+
+    std::string rep_table = report->AsTable();
+    std::ofstream ofs_table (profile_table, std::ofstream::out);
+    ofs_table << rep_table << std::endl;
+    ofs_table.close();
+
+    std::string rep_csv = report->AsCSV();
+    std::ofstream ofs_csv (profile_csv, std::ofstream::out);
+    ofs_csv << rep_csv << std::endl;
+    ofs_csv.close();
+}
+
 int MeraDrpRuntimeWrapper::GetNumInput(std::string model_dir) {
     // TVM does not support api to get number input of model.
     // This function calculate input number base on convention

apps/MeraDrpRuntimeWrapper.h

@@ -38,7 +38,9 @@ class MeraDrpRuntimeWrapper {
   template <typename T>
   void SetInput(int input_index, const T* data_ptr);
   void Run();
+  void Run(int freq_index);
   void ProfileRun(const std::string& profile_table, const std::string& profile_csv);
+  void ProfileRun(const std::string& profile_table, const std::string& profile_csv, int freq_index);
   int GetNumInput(std::string model_dir);
   InOutDataType GetInputDataType(int index);
   int GetNumOutput();