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| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Inc. team. | |
| # | |
| # 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. | |
| import argparse | |
| import json | |
| import os | |
| from tensorflow.core.protobuf.saved_model_pb2 import SavedModel | |
| # All paths are set with the intent you should run this script from the root of the repo with the command | |
| # python utils/check_copies.py | |
| REPO_PATH = "." | |
| # Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model) | |
| INTERNAL_OPS = [ | |
| "Assert", | |
| "AssignVariableOp", | |
| "EmptyTensorList", | |
| "MergeV2Checkpoints", | |
| "ReadVariableOp", | |
| "ResourceGather", | |
| "RestoreV2", | |
| "SaveV2", | |
| "ShardedFilename", | |
| "StatefulPartitionedCall", | |
| "StaticRegexFullMatch", | |
| "VarHandleOp", | |
| ] | |
| def onnx_compliancy(saved_model_path, strict, opset): | |
| saved_model = SavedModel() | |
| onnx_ops = [] | |
| with open(os.path.join(REPO_PATH, "utils", "tf_ops", "onnx.json")) as f: | |
| onnx_opsets = json.load(f)["opsets"] | |
| for i in range(1, opset + 1): | |
| onnx_ops.extend(onnx_opsets[str(i)]) | |
| with open(saved_model_path, "rb") as f: | |
| saved_model.ParseFromString(f.read()) | |
| model_op_names = set() | |
| # Iterate over every metagraph in case there is more than one (a saved model can contain multiple graphs) | |
| for meta_graph in saved_model.meta_graphs: | |
| # Add operations in the graph definition | |
| model_op_names.update(node.op for node in meta_graph.graph_def.node) | |
| # Go through the functions in the graph definition | |
| for func in meta_graph.graph_def.library.function: | |
| # Add operations in each function | |
| model_op_names.update(node.op for node in func.node_def) | |
| # Convert to list, sorted if you want | |
| model_op_names = sorted(model_op_names) | |
| incompatible_ops = [] | |
| for op in model_op_names: | |
| if op not in onnx_ops and op not in INTERNAL_OPS: | |
| incompatible_ops.append(op) | |
| if strict and len(incompatible_ops) > 0: | |
| raise Exception(f"Found the following incompatible ops for the opset {opset}:\n" + incompatible_ops) | |
| elif len(incompatible_ops) > 0: | |
| print(f"Found the following incompatible ops for the opset {opset}:") | |
| print(*incompatible_ops, sep="\n") | |
| else: | |
| print(f"The saved model {saved_model_path} can properly be converted with ONNX.") | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--saved_model_path", help="Path of the saved model to check (the .pb file).") | |
| parser.add_argument( | |
| "--opset", default=12, type=int, help="The ONNX opset against which the model has to be tested." | |
| ) | |
| parser.add_argument( | |
| "--framework", choices=["onnx"], default="onnx", help="Frameworks against which to test the saved model." | |
| ) | |
| parser.add_argument( | |
| "--strict", action="store_true", help="Whether make the checking strict (raise errors) or not (raise warnings)" | |
| ) | |
| args = parser.parse_args() | |
| if args.framework == "onnx": | |
| onnx_compliancy(args.saved_model_path, args.strict, args.opset) | |