Refactoring of MVAU and VVAU

src/finn/analysis/fpgadataflow/res_estimation.py

@@ -60,8 +60,8 @@ def res_estimation_complete(model):
     res_dict = {}
     for node in model.graph.node:
         if is_fpgadataflow_node(node) is True:
-            op_type = node.op_type
             inst = registry.getCustomOp(node)
+            op_type = inst.base_op_type()
             if op_type == "MatrixVectorActivation" or op_type == "VectorVectorActivation":
                 orig_restype = inst.get_nodeattr("resType")
                 res_dict[node.name] = []

src/finn/builder/build_dataflow_steps.py

@@ -569,7 +569,12 @@ def step_set_fifo_depths(model: ModelWrapper, cfg: DataflowBuildConfig):
         model = model.transform(GiveUniqueNodeNames())
         model = model.transform(GiveReadableTensorNames())
         if cfg.folding_config_file is not None:
-            model = model.transform(ApplyConfig(cfg.folding_config_file))
+            model = model.transform(
+                ApplyConfig(
+                    cfg.folding_config_file,
+                    node_filter=lambda x: x.op_type == "StreamingFIFO",
+                )
+            )
 
     # extract the final configuration and save it as json
     hw_attrs = [

src/finn/custom_op/fpgadataflow/hls/__init__.py

@@ -49,6 +49,7 @@
 from finn.custom_op.fpgadataflow.hls.streamingmaxpool_hls import StreamingMaxPool_hls
 from finn.custom_op.fpgadataflow.hls.tlastmarker_hls import TLastMarker_hls
 from finn.custom_op.fpgadataflow.hls.upsampler_hls import UpsampleNearestNeighbour_hls
+from finn.custom_op.fpgadataflow.hls.matrixvectoractivation_hls import MatrixVectorActivation_hls
 
 custom_op = dict()
 
@@ -73,3 +74,4 @@
 custom_op["StreamingMaxPool_hls"] = StreamingMaxPool_hls
 custom_op["TLastMarker_hls"] = TLastMarker_hls
 custom_op["UpsampleNearestNeighbour_hls"] = UpsampleNearestNeighbour_hls
+custom_op["MatrixVectorActivation_hls"] = MatrixVectorActivation_hls