diff --git a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py index afc2a2010fa41ba9431acbd03c18a6080cb296a0..56f3c0a8bb60ad5fba72e290177c10405a54f2d1 100644 --- a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py +++ b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py @@ -37,7 +37,6 @@ class InferBinaryStreamingFCLayer(Transformation): assert mw % simd == 0 wmem = mw * mh // (pe * simd) assert mw * mh == wmem * pe * simd - nf = mh // pe # see if we have any following thresholds consumer = model.find_consumer(mm_output) if consumer is not None and consumer.op_type == "MultiThreshold": @@ -46,7 +45,6 @@ class InferBinaryStreamingFCLayer(Transformation): mt_output = consumer.output[0] mt_thres = consumer.input[1] T = model.get_initializer(mt_thres) - tmem = nf assert T.shape[0] == 1 or T.shape[0] == mh odt = model.get_tensor_datatype(mt_output) if odt.bitwidth() == 1: @@ -70,13 +68,12 @@ class InferBinaryStreamingFCLayer(Transformation): MH=mh, SIMD=simd, PE=pe, - WMEM=wmem, - TMEM=tmem, inputDataType=idt.name, weightDataType=wdt.name, outputDataType=odt.name, ActVal=actval, binaryXnorMode=1, + noActivation=0, ) graph.node.insert(node_ind, new_node) # remove old nodes @@ -102,13 +99,12 @@ class InferBinaryStreamingFCLayer(Transformation): MH=mh, SIMD=simd, PE=pe, - WMEM=wmem, - TMEM=0, inputDataType=idt.name, weightDataType=wdt.name, outputDataType=odt.name, ActVal=0, binaryXnorMode=1, + noActivation=1, ) graph.node.insert(node_ind, new_node) # remove old node