diff --git a/src/finn/custom_op/fpgadataflow/fmpadding_batch.py b/src/finn/custom_op/fpgadataflow/fmpadding_batch.py index f9a9dc4340b18578550a9c453d90de86234d1cad..95ecc5f10525456e7f5a6d838e0850adaee5415f 100644 --- a/src/finn/custom_op/fpgadataflow/fmpadding_batch.py +++ b/src/finn/custom_op/fpgadataflow/fmpadding_batch.py @@ -48,7 +48,7 @@ class FMPadding_Batch(HLSCustomOp): simd = self.get_nodeattr("SIMD") batch_size = self.get_nodeattr("numInputVectors") exp_cycles = (channels / simd) * batch_size * odim * odim - return exp_cycles + return int(exp_cycles) def get_normal_input_shape(self): idim = self.get_nodeattr("ImgDim") diff --git a/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py b/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py index 1a75858880a072345ef942ca91feabf0bec9ab36..56f1a9d56d9da7057e3cbe61f3d92877e58087d6 100644 --- a/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py +++ b/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py @@ -187,7 +187,7 @@ class GlobalAccPool_Batch(HLSCustomOp): ch = self.get_nodeattr("NumChannels") pe = self.get_nodeattr("PE") folds = int(ch / pe) - return np.prod(self.get_folded_input_shape()[:-1]) + folds + return int(np.prod(self.get_folded_input_shape()[:-1]) + folds) def execute_node(self, context, graph): mode = self.get_nodeattr("exec_mode") diff --git a/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py b/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py index 4c772358648f402467cee628afe410d7bce83ede..53bcab993b25173c8620d7f4a6694a8efaf74c4d 100644 --- a/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py +++ b/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py @@ -99,7 +99,7 @@ class StreamingMaxPool_Batch(HLSCustomOp): # derived from StreamingMaxPool_Batch loop nest k = self.get_nodeattr("PoolDim") ifm_dim = self.get_nodeattr("ImgDim") - return ifm_dim * (ifm_dim + (ifm_dim / k)) + return int(ifm_dim * (ifm_dim + (ifm_dim / k))) def get_instream_width(self): dt_bits = self.get_input_datatype().bitwidth()