Hardware Custom Op Registry Refactoring and Brainsmith Integration

notebooks/advanced/2_custom_op.ipynb

@@ -432,10 +432,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from qonnx.custom_op.registry import getCustomOp\n",
+    "from finn.util.basic import getHWCustomOp\n",
     "\n",
     "# get FINN wrapper for this node, with all the functionality\n",
-    "op_inst = getCustomOp(mixedop_graph.model.graph.node[0])\n",
+    "op_inst = getHWCustomOp(mixedop_graph.model.graph.node[0])\n",
     "print(\"Available functions: \" + str(dir(op_inst)))\n",
     "# query some attributes\n",
     "print(\"codegen_dir: \" + op_inst.get_nodeattr(\"codegen_dir\"))\n",
@@ -471,7 +471,7 @@
     "        # check node type before we do anything\n",
     "        if node.op_type == \"MyMixedPowerOp\":\n",
     "            # get FINN wrapper for this node, with all the functions\n",
-    "            op_inst = getCustomOp(node)\n",
+    "            op_inst = getHWCustomOp(node)\n",
     "            if not os.path.isdir(op_inst.get_nodeattr(\"codegen_dir\")):\n",
     "                # call the codegen function we defined\n",
     "                # this will modify the underlying node by setting attribute\n",
@@ -512,7 +512,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "new_op_inst = getCustomOp(mixedop_graph_new.graph.node[0])\n",
+    "new_op_inst = getHWCustomOp(mixedop_graph_new.graph.node[0])\n",
     "codegen_dir = new_op_inst.get_nodeattr(\"codegen_dir\")\n",
     "print(codegen_dir)"
    ]

notebooks/advanced/3_folding.ipynb

@@ -271,7 +271,7 @@
     "\n",
     "In the first step, we left the `PE` & `SIMD` values for all the layers on default (=1) to establish a baseline and measure the estimated clock cycles and resource utilization for each of the individual layers.\n",
     "\n",
-    "To set `PE` & `SIMD`, we will utilize functionality from the FINN compiler. Each layer type has a Python wrapper which can be instantiated using the `getCustomOp()` function. The wrapper offers several helper functions like `get_nodeattr()` and `set_nodeattr()` to access and set the attributes of a node."
+    "To set `PE` & `SIMD`, we will utilize functionality from the FINN compiler. Each layer type has a Python wrapper which can be instantiated using the `getHWCustomOp()` function. The wrapper offers several helper functions like `get_nodeattr()` and `set_nodeattr()` to access and set the attributes of a node."
    ]
   },
   {
@@ -280,12 +280,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from qonnx.custom_op.registry import getCustomOp\n",
+    "from finn.util.basic import getHWCustomOp\n",
     "\n",
     "list_of_mvaus = model.get_nodes_by_op_type(\"MVAU_hls\")\n",
     "mvau0 = list_of_mvaus[0]\n",
     "\n",
-    "mvau0_inst = getCustomOp(mvau0)\n",
+    "mvau0_inst = getHWCustomOp(mvau0)\n",
     "\n",
     "# Get the node attributes to check the current setting\n",
     "print(\"The parallelization parameters of %s were: \" % mvau0.name)\n",
@@ -444,7 +444,7 @@
     "list_of_mvaus = model_orig.get_nodes_by_op_type(\"MVAU_hls\")\n",
     "print(\"In the original model (pe=simd=1): \")\n",
     "for mvau in list_of_mvaus:\n",
-    "    mvau_inst = getCustomOp(mvau)\n",
+    "    mvau_inst = getHWCustomOp(mvau)\n",
     "    print(\"Layer: \" + mvau.name)\n",
     "    print(\"Input shape: \" + str(mvau_inst.get_folded_input_shape()))\n",
     "    print(\"Output shape: \" + str(mvau_inst.get_folded_output_shape()))"
@@ -460,7 +460,7 @@
     "list_of_mvaus = model_updated.get_nodes_by_op_type(\"MVAU_hls\")\n",
     "print(\"In the original model (pe=simd=1): \")\n",
     "for mvau in list_of_mvaus:\n",
-    "    mvau_inst = getCustomOp(mvau)\n",
+    "    mvau_inst = getHWCustomOp(mvau)\n",
     "    print(\"Layer: \" + mvau.name)\n",
     "    print(\"Input shape: \" + str(mvau_inst.get_folded_input_shape()))\n",
     "    print(\"Output shape: \" + str(mvau_inst.get_folded_output_shape()))"
@@ -515,7 +515,7 @@
     "list_of_mvaus = model_orig.get_nodes_by_op_type(\"MVAU_hls\")\n",
     "print(\"In the original model (pe=simd=1): \")\n",
     "for mvau in list_of_mvaus:\n",
-    "    mvau_inst = getCustomOp(mvau)\n",
+    "    mvau_inst = getHWCustomOp(mvau)\n",
     "    print(\"Layer: \" + mvau.name)\n",
     "    print(\"Input stream width: \" + str(mvau_inst.get_instream_width()))\n",
     "    print(\"Output stream width: \" + str(mvau_inst.get_outstream_width()))"
@@ -545,7 +545,7 @@
     "list_of_mvaus = model_updated.get_nodes_by_op_type(\"MVAU_hls\")\n",
     "print(\"In the original model (pe=simd=1): \")\n",
     "for mvau in list_of_mvaus:\n",
-    "    mvau_inst = getCustomOp(mvau)\n",
+    "    mvau_inst = getHWCustomOp(mvau)\n",
     "    print(\"Layer: \" + mvau.name)\n",
     "    print(\"Input stream width: \" + str(mvau_inst.get_instream_width()))\n",
     "    print(\"Output stream width: \" + str(mvau_inst.get_outstream_width()))"

notebooks/end2end_example/bnn-pynq/cnv_end2end_example.ipynb

@@ -294,7 +294,7 @@
     ")\n",
     "from finn.transformation.move_reshape import RemoveCNVtoFCFlatten\n",
     "from finn.transformation.fpgadataflow.specialize_layers import SpecializeLayers\n",
-    "from qonnx.custom_op.registry import getCustomOp\n",
+    "from finn.util.basic import getHWCustomOp\n",
     "from qonnx.transformation.infer_data_layouts import InferDataLayouts\n",
     "\n",
     "model = ModelWrapper(build_dir + \"/end2end_cnv_w1a1_streamlined.onnx\")\n",
@@ -315,7 +315,7 @@
     "parent_model = model.transform(CreateDataflowPartition())\n",
     "parent_model.save(build_dir + \"/end2end_cnv_w1a1_dataflow_parent.onnx\")\n",
     "sdp_node = parent_model.get_nodes_by_op_type(\"StreamingDataflowPartition\")[0]\n",
-    "sdp_node = getCustomOp(sdp_node)\n",
+    "sdp_node = getHWCustomOp(sdp_node)\n",
     "dataflow_model_filename = sdp_node.get_nodeattr(\"model\")\n",
     "# save the dataflow partition with a different name for easier access\n",
     "# and specialize the layers to HLS variants\n",
@@ -384,15 +384,15 @@
     "    (5, 1, [3]),\n",
     "]\n",
     "for fcl, (pe, simd, ififodepth) in zip(fc_layers, folding):\n",
-    "    fcl_inst = getCustomOp(fcl)\n",
+    "    fcl_inst = getHWCustomOp(fcl)\n",
     "    fcl_inst.set_nodeattr(\"PE\", pe)\n",
     "    fcl_inst.set_nodeattr(\"SIMD\", simd)\n",
     "    fcl_inst.set_nodeattr(\"inFIFODepths\", ififodepth)\n",
     "\n",
     "# use same SIMD values for the sliding window operators\n",
     "swg_layers = model.get_nodes_by_op_type(\"ConvolutionInputGenerator_rtl\")\n",
     "for i in range(len(swg_layers)):\n",
-    "    swg_inst = getCustomOp(swg_layers[i])\n",
+    "    swg_inst = getHWCustomOp(swg_layers[i])\n",
     "    simd = folding[i][1]\n",
     "    swg_inst.set_nodeattr(\"SIMD\", simd)\n",
     "\n",

notebooks/end2end_example/bnn-pynq/tfc_end2end_example.ipynb

@@ -499,9 +499,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from qonnx.custom_op.registry import getCustomOp\n",
+    "from finn.util.basic import getHWCustomOp\n",
     "sdp_node = parent_model.get_nodes_by_op_type(\"StreamingDataflowPartition\")[0]\n",
-    "sdp_node = getCustomOp(sdp_node)\n",
+    "sdp_node = getHWCustomOp(sdp_node)\n",
     "dataflow_model_filename = sdp_node.get_nodeattr(\"model\")\n",
     "showInNetron(dataflow_model_filename)"
    ]
@@ -543,7 +543,7 @@
    "outputs": [],
    "source": [
     "thresh_node = model.get_nodes_by_op_type(\"Thresholding\")[0]\n",
-    "thresh_node_inst = getCustomOp(thresh_node)\n",
+    "thresh_node_inst = getHWCustomOp(thresh_node)\n",
     "thresh_node_inst.set_nodeattr(\"preferred_impl_style\", \"hls\")"
    ]
   },
@@ -634,7 +634,7 @@
    "outputs": [],
    "source": [
     "fc0 = model.graph.node[1]\n",
-    "fc0w = getCustomOp(fc0)\n",
+    "fc0w = getHWCustomOp(fc0)\n",
     "\n",
     "print(\"CustomOp wrapper is of class \" + fc0w.__class__.__name__)\n",
     "\n",
@@ -664,7 +664,7 @@
     "    (10, 8, [64], [10], \"distributed\"),\n",
     "]\n",
     "for fcl, (pe, simd, ififo, ofifo, ramstyle) in zip(fc_layers, config):\n",
-    "    fcl_inst = getCustomOp(fcl)\n",
+    "    fcl_inst = getHWCustomOp(fcl)\n",
     "    fcl_inst.set_nodeattr(\"PE\", pe)\n",
     "    fcl_inst.set_nodeattr(\"SIMD\", simd)\n",
     "    fcl_inst.set_nodeattr(\"inFIFODepths\", ififo)\n",
@@ -673,7 +673,7 @@
     "    \n",
     "# set parallelism for input quantizer to be same as first layer's SIMD\n",
     "inp_qnt_node = model.get_nodes_by_op_type(\"Thresholding_hls\")[0]\n",
-    "inp_qnt = getCustomOp(inp_qnt_node)\n",
+    "inp_qnt = getHWCustomOp(inp_qnt_node)\n",
     "inp_qnt.set_nodeattr(\"PE\", 49)"
    ]
   },
@@ -796,7 +796,7 @@
    "outputs": [],
    "source": [
     "model = ModelWrapper(build_dir + \"/tfc_w1_a1_post_synthesis.onnx\")\n",
-    "sdp_node_middle = getCustomOp(model.graph.node[1])\n",
+    "sdp_node_middle = getHWCustomOp(model.graph.node[1])\n",
     "postsynth_layers = sdp_node_middle.get_nodeattr(\"model\")\n",
     "\n",
     "showInNetron(postsynth_layers)"

notebooks/end2end_example/bnn-pynq/tfc_end2end_verification.ipynb

@@ -220,10 +220,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from qonnx.custom_op.registry import getCustomOp\n",
+    "from finn.util.basic import getHWCustomOp\n",
     "\n",
     "fc0 = model_for_cppsim.graph.node[1]\n",
-    "fc0w = getCustomOp(fc0)\n",
+    "fc0w = getHWCustomOp(fc0)\n",
     "code_gen_dir = fc0w.get_nodeattr(\"code_gen_dir_cppsim\")\n",
     "!ls {code_gen_dir}"
    ]
@@ -272,7 +272,7 @@
     "parent_model = ModelWrapper(build_dir+\"/tfc_w1_a1_dataflow_parent.onnx\")\n",
     "sdp_node = parent_model.graph.node[1]\n",
     "child_model = build_dir + \"/tfc_w1_a1_for_cppsim.onnx\"\n",
-    "getCustomOp(sdp_node).set_nodeattr(\"model\", child_model)\n",
+    "getHWCustomOp(sdp_node).set_nodeattr(\"model\", child_model)\n",
     "output_dict = oxe.execute_onnx(parent_model, input_dict)\n",
     "output_cppsim = output_dict[list(output_dict.keys())[0]]\n",
     "\n",
@@ -350,7 +350,7 @@
     "# parent model\n",
     "model_for_rtlsim = ModelWrapper(build_dir + \"/tfc_w1_a1_dataflow_parent.onnx\")\n",
     "# reference child model\n",
-    "sdp_node = getCustomOp(model_for_rtlsim.graph.node[1])\n",
+    "sdp_node = getHWCustomOp(model_for_rtlsim.graph.node[1])\n",
     "sdp_node.set_nodeattr(\"model\", build_dir + \"/tfc_w1_a1_dataflow_child.onnx\")\n",
     "\n",
     "model_for_rtlsim = model_for_rtlsim.transform(SetExecMode(\"rtlsim\"))"
@@ -416,7 +416,7 @@
     "# parent model\n",
     "model_for_rtlsim = ModelWrapper(build_dir + \"/tfc_w1_a1_dataflow_parent.onnx\")\n",
     "# reference child model\n",
-    "sdp_node = getCustomOp(model_for_rtlsim.graph.node[1])\n",
+    "sdp_node = getHWCustomOp(model_for_rtlsim.graph.node[1])\n",
     "sdp_node.set_nodeattr(\"model\", build_dir + \"/tfc_w1_a1_dataflow_child.onnx\")"
    ]
   },

setup.cfg

@@ -94,6 +94,11 @@ testing =
 [options.entry_points]
 console_scripts =
     build_dataflow = finn.builder.build_dataflow:main
+
+# Brainsmith plugin integration
+brainsmith.plugins =
+    finn = finn.util.brainsmith_integration:register_all
+
 # Add here console scripts like:
 # console_scripts =
 #     script_name = finn.module:function

src/finn/analysis/fpgadataflow/dataflow_performance.py

@@ -27,8 +27,7 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from qonnx.custom_op.registry import getCustomOp
-
+from finn.util.basic import getHWCustomOp
 from finn.util.fpgadataflow import is_hls_node, is_rtl_node
 
 
@@ -54,7 +53,7 @@ def dataflow_performance(model):
 
     for node in model.graph.node:
         if is_hls_node(node) or is_rtl_node(node):
-            inst = getCustomOp(node)
+            inst = getHWCustomOp(node, model)
             node_cycles = int(inst.get_nodeattr("cycles_estimate"))
             if node_cycles > max_cycles:
                 max_cycles = node_cycles

src/finn/analysis/fpgadataflow/exp_cycles_per_layer.py

@@ -27,8 +27,7 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import qonnx.custom_op.registry as registry
-
+from finn.util.basic import getHWCustomOp
 from finn.util.fpgadataflow import is_hls_node, is_rtl_node
 
 
@@ -43,7 +42,7 @@ def exp_cycles_per_layer(model):
     cycle_dict = {}
     for node in model.graph.node:
         if is_hls_node(node) or is_rtl_node(node):
-            inst = registry.getCustomOp(node)
+            inst = getHWCustomOp(node, model)
             cycle_dict[node.name] = int(inst.get_exp_cycles())
 
     return cycle_dict

src/finn/analysis/fpgadataflow/floorplan_params.py

@@ -27,8 +27,7 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from qonnx.custom_op.registry import getCustomOp
-
+from finn.util.basic import getHWCustomOp
 from finn.util.fpgadataflow import is_fpgadataflow_node
 
 
@@ -47,7 +46,7 @@ def floorplan_params(model):
     }
     for node in model.graph.node:
         if is_fpgadataflow_node(node):
-            node_inst = getCustomOp(node)
+            node_inst = getHWCustomOp(node, model)
             node_slr = node_inst.get_nodeattr("slr")
             node_pid = node_inst.get_nodeattr("partition_id")
             node_mport = node_inst.get_nodeattr("mem_port")

src/finn/analysis/fpgadataflow/hls_synth_res_estimation.py

@@ -26,10 +26,10 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 import os
-import qonnx.custom_op.registry as registry
 import warnings
 import xml.etree.ElementTree as ET
 
+from finn.util.basic import getHWCustomOp
 from finn.util.fpgadataflow import is_hls_node
 
 
@@ -52,7 +52,7 @@ def hls_synth_res_estimation(model):
             res_dict[node.name]["LUT"] = 0
             res_dict[node.name]["DSP48E"] = 0
             res_dict[node.name]["URAM"] = 0
-            inst = registry.getCustomOp(node)
+            inst = getHWCustomOp(node, model)
             code_gen_dir = inst.get_nodeattr("code_gen_dir_ipgen")
             if code_gen_dir == "":
                 warnings.warn(

src/finn/analysis/fpgadataflow/op_and_param_counts.py

@@ -26,9 +26,10 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import qonnx.custom_op.registry as registry
 from qonnx.util.basic import is_finn_op
 
+from finn.util.basic import getHWCustomOp
+
 
 def aggregate_dict_keys(res_dict):
     total_dict = {}
@@ -52,7 +53,7 @@ def op_and_param_counts(model):
     ret_dict = {}
     for node in model.graph.node:
         if is_finn_op(node.domain):
-            inst = registry.getCustomOp(node)
+            inst = getHWCustomOp(node, model)
             if hasattr(inst, "get_op_and_param_counts"):
                 node_op_and_param_counts = inst.get_op_and_param_counts()
                 ret_dict[node.name] = node_op_and_param_counts

src/finn/analysis/fpgadataflow/post_synth_res.py

@@ -30,8 +30,8 @@
 import os
 import xml.etree.ElementTree as ET
 from qonnx.core.modelwrapper import ModelWrapper
-from qonnx.custom_op.registry import getCustomOp
 
+from finn.util.basic import getHWCustomOp
 from finn.util.fpgadataflow import is_hls_node, is_rtl_node
 
 
@@ -122,7 +122,7 @@ def get_instance_stats(inst_name):
 
     for node in model.graph.node:
         if node.op_type == "StreamingDataflowPartition":
-            sdp_model = ModelWrapper(getCustomOp(node).get_nodeattr("model"))
+            sdp_model = ModelWrapper(getHWCustomOp(node, model).get_nodeattr("model"))
             sdp_res_dict = post_synth_res(sdp_model, synth_report_filename)
             res_dict.update(sdp_res_dict)
         elif is_hls_node(node) or is_rtl_node(node):

src/finn/analysis/fpgadataflow/res_estimation.py

@@ -26,8 +26,7 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import qonnx.custom_op.registry as registry
-
+from finn.util.basic import getHWCustomOp
 from finn.util.fpgadataflow import is_hls_node, is_rtl_node
 
 
@@ -42,7 +41,7 @@ def res_estimation(model, fpgapart):
     res_dict = {}
     for node in model.graph.node:
         if is_hls_node(node) or is_rtl_node(node):
-            inst = registry.getCustomOp(node)
+            inst = getHWCustomOp(node, model)
             res_dict[node.name] = inst.node_res_estimation(fpgapart)
 
     return res_dict
@@ -60,7 +59,7 @@ def res_estimation_complete(model, fpgapart):
     res_dict = {}
     for node in model.graph.node:
         if is_hls_node(node) or is_rtl_node(node):
-            inst = registry.getCustomOp(node)
+            inst = getHWCustomOp(node, model)
             op_type = node.op_type
             if op_type.startswith("MVAU") or op_type.startswith("VVAU"):
                 orig_restype = inst.get_nodeattr("resType")