[Refactor] make varname more explanatory in InsertDWC

src/finn/transformation/fpgadataflow/insert_dwc.py

@@ -44,8 +44,8 @@ class InsertDWC(Transformation):
         for n in graph.node:
             node_ind += 1
             if _suitable_node(n):
-                for n_output in n.output:
-                    consumers = model.find_consumers(n_output)
+                for output_name in n.output:
+                    consumers = model.find_consumers(output_name)
                     if consumers is None:
                         continue
                     if len(consumers) > 1:
@@ -61,14 +61,16 @@ class InsertDWC(Transformation):
                         n0_out_shape = n0.get_folded_output_shape()
 
                         # If FC and external mem, it could be connected to input 1
-                        if (consumer.op_type == "StreamingFCLayer_Batch" and 
-                            n1.get_nodeattr("mem_mode") == "external"):
+                        if (
+                            consumer.op_type == "StreamingFCLayer_Batch"
+                            and n1.get_nodeattr("mem_mode") == "external"
+                        ):
                             # get input idx
                             in_idx = None
                             for idx, n_input in enumerate(consumer.input):
-                                if n_output == n_input:
+                                if output_name == n_input:
                                     in_idx = idx
-                            assert in_idx is not None,"Malformed model"
+                            assert in_idx is not None, "Malformed model"
                             n1_in_shape = n1.get_folded_input_shape(in_idx)
                         else:
                             n1_in_shape = n1.get_folded_input_shape()
@@ -95,7 +97,7 @@ class InsertDWC(Transformation):
 
                             dwc_node = oh.make_node(
                                 "StreamingDataWidthConverter_Batch",
-                                [n_output],
+                                [output_name],
                                 [dwc_output_tensor.name],
                                 domain="finn.custom_op.fpgadataflow",
                                 backend="fpgadataflow",
@@ -109,7 +111,7 @@ class InsertDWC(Transformation):
 
                             # set dwc output tensor as new input tensor of second node
                             for idx, inp in enumerate(consumer.input):
-                                if inp == n_output:
+                                if inp == output_name:
                                     consumer.input[idx] = dwc_output_tensor.name
 
         return (model, graph_modified)