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From GitBox <...@apache.org>
Subject [GitHub] [incubator-tvm] deepakbabel23 commented on a change in pull request #5617: [TENSORFLOW]StatefulPartitionedCall/PartitionedCall Ops support added
Date Thu, 28 May 2020 07:29:45 GMT

deepakbabel23 commented on a change in pull request #5617:
URL: https://github.com/apache/incubator-tvm/pull/5617#discussion_r431635377



##########
File path: python/tvm/relay/frontend/tensorflow.py
##########
@@ -2896,15 +2903,29 @@ def _parse_import_prerequisites(self, graph):
         """
         missing_operators = set()
         for node in graph.node:
+            try:
+                from tensorflow.python.framework import op_def_registry
+            except ImportError as e:
+                raise ImportError(
+                    "Unable to import tensorflow which is required {}".format(e))
+            getOpDef = op_def_registry._registered_ops.get if hasattr(op_def_registry,\
+                        "_registered_ops") else op_def_registry.get
+            op_def = getOpDef(node.op)
             if node.op == "Placeholder" or node.op == 'PlaceholderWithDefault':
                 pass
             elif node.op == "Const":
                 pass
+            elif node.op in ["PartitionedCall", "StatefulPartitionedCall"]:
+                pass
             else:
                 if any([node.op in t for t in [_identity_list, _convert_map,
                                                _convert_map_rnn,
                                                _control_flow_nodes]]):
                     pass
+                elif op_def is not None and op_def.is_stateful:
+                    raise Exception("Found a stateful operator in this graph {}. "\

Review comment:
       Yes sure, It will support the aforesaid purpose. You can review once after I handle
this in the new implementation.




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