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chore: import upstream snapshot with attribution
2026-07-13 12:14:16 +08:00

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Python

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =============================================================================
"""Provides a proper python API for the symbols exported through swig."""
from tensorflow.python.grappler import _pywrap_model_analyzer as tf_wrap
def GenerateModelReport(metagraph, assume_valid_feeds=True, debug=False):
"""Report what's known statically about each node in the provided metagraph.
Args:
metagraph: A TensorFlow MetaGraphDef.
assume_valid_feeds: If True, assume that the shape of the fed nodes is valid
debug: Add some information useful for debugging.
Returns:
A string containing the report.
"""
return tf_wrap.GenerateModelReport(
metagraph.SerializeToString(), assume_valid_feeds, debug)