[GitHub] [tvm] wx3000 commented on a change in pull request #7498: [TENSORFLOW] Tensorflow 2.x support

[GitBox <gi...@apache.org>]

wx3000 commented on a change in pull request #7498:
URL: https://github.com/apache/tvm/pull/7498#discussion_r580712245



##########
File path: python/tvm/relay/frontend/tensorflow.py
##########
@@ -3682,6 +3729,30 @@ def from_tensorflow(graph, layout="NHWC", shape=None, outputs=None):
     params : dict of str to tvm.nd.NDArray
         Dict of converted parameters stored in tvm.nd.NDArray format
     """
+    from tensorflow.python.eager.function import ConcreteFunction
+
+    if isinstance(graph, ConcreteFunction):

Review comment:
       would it be better if we create a wrapper over from_tensorflow_concrete_function() instead of overloading the parameter "graph" to be either GraphDef or ConcreteFunction? 
   
   Another question: Is ConcreteFunction the right entry point? Why not start from the saved_model format? When TVM is used to compile a model for inference, it starts from a saved_model. This way there is no need to use _build_signature_def in order to optimize the graph. Maybe _build_signature_def can be part of the test utility code.

##########
File path: python/tvm/relay/frontend/tensorflow.py
##########
@@ -3682,6 +3729,30 @@ def from_tensorflow(graph, layout="NHWC", shape=None, outputs=None):
     params : dict of str to tvm.nd.NDArray
         Dict of converted parameters stored in tvm.nd.NDArray format
     """
+    from tensorflow.python.eager.function import ConcreteFunction
+
+    if isinstance(graph, ConcreteFunction):
+        try:
+            from tensorflow.python.framework import convert_to_constants
+            from tensorflow.core.protobuf import config_pb2
+        except ImportError as e:
+            raise ImportError("Unable to import tensorflow which is required {}".format(e))
+        concrete_func = graph
+        graph = convert_to_constants.convert_variables_to_constants_v2(concrete_func).graph
+        signature = _build_signature_def(graph, concrete_func.inputs, concrete_func.outputs)
+        graph_def = graph.as_graph_def()
+
+        # Some optimization
+        config = config_pb2.ConfigProto()
+        rewriter_config = config.graph_options.rewrite_options
+        rewriter_config.optimizers[:] = [
+            "debug_stripper",
+            "arithmetic",
+            "dependency",
+            "arithmetic",

Review comment:
       typo: duplicate of line 3750




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