Fix small bugs in transformations

src/finn/transformation/fpgadataflow/insert_dwc.py

@@ -95,16 +95,16 @@ def apply(self, model):
                                     in_idx = idx
                             assert in_idx is not None, "Malformed model"
                             n1_in_shape = n1.get_folded_input_shape(in_idx)
+                            dwc_out_width = n1.get_instream_width(in_idx)
                         else:
                             # use default folded input shape
                             n1_in_shape = n1.get_folded_input_shape()
+                            dwc_out_width = n1.get_instream_width()
 
                         if n0_out_shape[-1] != n1_in_shape[-1]:
                             graph_modified = True
                             # determine dwc inwidth
                             dwc_in_width = n0.get_outstream_width()
-                            # determine dwc outwidth
-                            dwc_out_width = n1.get_instream_width()
                             node_optype = "StreamingDataWidthConverter"
 
                             # determine shape for dwc

src/finn/transformation/fpgadataflow/set_folding.py

@@ -114,6 +114,7 @@ def apply(self, model):
         simd_ops = [
             "DownSampler_hls",
             "FMPadding_hls",
+            "FMPadding_rtl",
             "FMPadding_Pixel_hls",
             "ConvolutionInputGenerator_hls",
             "ConvolutionInputGenerator_rtl",

src/finn/transformation/streamline/reorder.py

@@ -631,6 +631,9 @@ def apply(self, model):
                 prod0 = model.find_producer(in0)
                 if prod0 is None:
                     continue
+                # Ignore if producer is fork
+                if model.is_fork_node(prod0):
+                    continue
 
                 if prod0.op_type in ["Mul", "Add", "Div"]:
                     # check if second input of producer is an initializer