wx3000 commented on a change in pull request #7498:
URL: https://github.com/apache/tvm/pull/7498#discussion_r580712245
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File path: python/tvm/relay/frontend/tensorflow.py
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@@ -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() instead
of overloading the parameter "graph" to be either GraphDef or ConcreteFunction?
Another question: Is ConcreteFunction the right parameter for the TF front
end parser? How about start from the saved_model format? When TVM is used to
compile a model for inference, it starts from a saved_model. This way perhaps
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 if we have test
which needs to start from ConcreteFunction;
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