Merge pull request #1019 from xadupre/output

Remove unnecessary deepcopy when accessing output from class Node

Author: guschmue

tf2onnx/graph.py

@@ -60,7 +60,7 @@ def input(self, val):
 
     @property
     def output(self):
-        return copy.deepcopy(self._output)
+        return self._output
 
     @output.setter
     def output(self, val):
@@ -71,7 +71,7 @@ def output(self, val):
         for o in self._output:
             del self.graph._output_to_node_name[o]
 
-        self._output = val
+        self._output = val.copy()
         for o in self._output:
             utils.make_sure(o not in self.graph._output_to_node_name, "output %s already in output mapping", o)
             self.graph._output_to_node_name[o] = self.name

tf2onnx/onnx_opset/controlflow.py

@@ -515,7 +515,9 @@ def version_7(cls, ctx, node, **kwargs):
 
         output_shapes = node.output_shapes
         output_dtypes = node.output_dtypes
-        output_names = node.output
+        # node.output must be copied as some element
+        # may be removed from output_names below
+        output_names = node.output.copy()
 
         # Make maximum_iterations int64 and replace -1(tf) with maxsize(onnx). If the const node has no other consumers,
         # modify it in place. Otherwise, make a new const node and leave the original unchanged.

tf2onnx/onnx_opset/generator.py

@@ -186,7 +186,8 @@ def version_8(cls, ctx, node, **kwargs):
 class IteratorGetNext:
     @classmethod
     def version_8(cls, ctx, node, **kwargs):
-        output_names = node.output
+        output_names = node.output.copy()  # to make sure remove_node
+                                           # does not alter the list
         type_0 = ctx.get_dtype(output_names[0])
         type_1 = ctx.get_dtype(output_names[1])
         shape_0 = ctx.get_shape(output_names[0])
@@ -200,7 +201,8 @@ def version_8(cls, ctx, node, **kwargs):
 class QueueDequeueManyV2:
     @classmethod
     def version_8(cls, ctx, node, **kwargs):
-        outputs = node.output
+        outputs = node.output.copy()  # copy to make remove_node
+                                      # does not alter the list
         shapes = node.output_shapes
         dtypes = node.output_dtypes
         ctx.remove_node(node.name)

tf2onnx/onnx_opset/nn.py

@@ -666,6 +666,7 @@ def version_6(cls, ctx, node, **kwargs):
         consumers = [ctx.find_output_consumers(output_name) for output_name in node.output[1:]]
         if not any(consumers):
             new_output = [node.output[0]]
+            # the setter makes a copy of new_output
             node.output = new_output
 
         conv_convert_inputs(ctx, node, with_kernel=False)

tf2onnx/optimizer/back_to_back_optimizer.py

@@ -237,6 +237,7 @@ def _optimize_conv_batchnorm_fusion(g, node, consumer_nodes):
         node2_shape = g.get_shape(node2.output[0])
         node2_dtype = g.get_dtype(node2.output[0])
         g.remove_node(node2.name)
+        # the setter makes a copy
         node.output = node2_output
         g.set_shape(node2_output[0], node2_shape)
         g.set_dtype(node2_output[0], node2_dtype)