fix comment

Author: RandyShuai

tf2onnx/custom_opsets/onnx_ml.py

@@ -10,15 +10,15 @@
 @tf_op("HashTableV2")
 class HashTable:
     @classmethod
-    def version_1(cls, ctx, node, **kwargs):
+    def version_8(cls, ctx, node, **kwargs):
         """ HashTable will be removed """
         pass
 
 
 @tf_op("LookupTableFindV2")
 class LookupTableFind:
     @classmethod
-    def version_1(cls, ctx, node, **kwargs):
+    def version_8(cls, ctx, node, **kwargs):
         """ convert lookup to category mapper """
         table_node = node.inputs[0]
         file_path = table_node.get_attr_value("shared_name")[11:-6]

tf2onnx/onnx_opset/controlflow.py

@@ -369,13 +369,13 @@ def version_9(cls, ctx, node, **kwargs):
 @tf_op("IteratorV2")
 class Iterator:
     @classmethod
-    def version_1(cls, ctx, node, **kwargs):
+    def version_8(cls, ctx, node, **kwargs):
         ctx.remove_node(node.name)
 
 @tf_op("IteratorGetNext")
 class IteratorGetNext:
     @classmethod
-    def version_1(cls, ctx, node, **kwargs):
+    def version_8(cls, ctx, node, **kwargs):
         output_names = node.output
         ctx.remove_node(node.name)
         output_types = list(node.get_attr('output_types').ints)

tf2onnx/tfonnx.py

@@ -80,7 +80,8 @@ def tflist_to_onnx(node_list, shape_override):
                 if dtype:
                     if not isinstance(dtype, list):
                         dtypes[node.name] = utils.map_tf_dtype(dtype)
-            elif a in ["output_type", "output_dtype", "out_type", "Tidx", "out_idx"]:
+            elif a in ["output_type", "output_dtype", "out_type", "Tidx",
+                       "out_idx", "key_dtype", "value_dtype", "Tin", "Tout"]:
                 # Tidx is used by Range
                 # out_idx is used by ListDiff
                 attr[a] = utils.map_tf_dtype(utils.get_tf_node_attr(node, a))
@@ -99,8 +100,6 @@ def tflist_to_onnx(node_list, shape_override):
                 continue
             elif a in ignored_attr:
                 continue
-            elif a in ["key_dtype", "value_dtype", "Tin", "Tout"]:
-                attr[a] = utils.map_tf_dtype(utils.get_tf_node_attr(node, a))
             elif a == "output_types":
                 attr[a] = [utils.map_tf_dtype(v) for v in utils.get_tf_node_attr(node, a)]
             elif a == "output_shapes":