
"""simple docstring"""

import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
UpperCamelCase			:       Tuple									=				[
    "kernels/rwkv/wkv_cuda.cu",
    "kernels/rwkv/wkv_op.cpp",
    "kernels/deformable_detr/ms_deform_attn.h",
    "kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh",
    "models/graphormer/algos_graphormer.pyx",
]






def 							A		(       snake_case   :Union[str, Any]	)   ->			Union[str, Any]:
 # Test all the extensions added in the setup
 for file in FILES_TO_FIND:
  if not (transformers_path / file).exists():
   return False
 return True


if __name__ == "__main__":
      UpperCamelCase			:       str									=				argparse.ArgumentParser()
      parser.add_argument("--check_lib", action="store_true", help="Whether to check the build or the actual package.")
      UpperCamelCase			:       List[Any]									=				parser.parse_args()
      if args.check_lib:
            UpperCamelCase			:       Union[str, Any]									=				importlib.import_module("transformers")
            UpperCamelCase			:       str									=				Path(transformers_module.__file__).parent
      else:
            UpperCamelCase			:       Union[str, Any]									=				Path.cwd() / "build/lib/transformers"
      if not test_custom_files_are_present(transformers_path):
            raise ValueError("The built release does not contain the custom files. Fix this before going further!")





"""simple docstring"""

import argparse
import json
import os

from tensorflow.core.protobuf.saved_model_pba 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
UpperCamelCase			:       Tuple									=				"."

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
UpperCamelCase			:       Dict									=				[
    "Assert",
    "AssignVariableOp",
    "EmptyTensorList",
    "MergeV2Checkpoints",
    "ReadVariableOp",
    "ResourceGather",
    "RestoreV2",
    "SaveV2",
    "ShardedFilename",
    "StatefulPartitionedCall",
    "StaticRegexFullMatch",
    "VarHandleOp",
]






def 							A		(       snake_case   :List[str]       ,      snake_case   :Optional[int]       ,      snake_case   :Optional[Any]	)   ->			Any:
 __UpperCamelCase       						= SavedModel()
 __UpperCamelCase       						= []

 with open(os.path.join(snake_case       ,      'utils'       ,      'tf_ops'       ,      'onnx.json'	)	) as f:
  __UpperCamelCase       						= json.load(snake_case	)['opsets']

 for i in range(1       ,      opset + 1	):
  onnx_ops.extend(onnx_opsets[str(snake_case	)]	)

 with open(snake_case       ,      'rb'	) as f:
  saved_model.ParseFromString(f.read()	)

 __UpperCamelCase       						= 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
 __UpperCamelCase       						= sorted(snake_case	)
 __UpperCamelCase       						= []

 for op in model_op_names:
  if op not in onnx_ops and op not in INTERNAL_OPS:
   incompatible_ops.append(snake_case	)

 if strict and len(snake_case	) > 0:
  raise Exception(f'Found the following incompatible ops for the opset {opset}:\n' + incompatible_ops	)
 elif len(snake_case	) > 0:
  print(f'Found the following incompatible ops for the opset {opset}:'	)
  print(*snake_case       ,      sep='\n'	)
 else:
  print(f'The saved model {saved_model_path} can properly be converted with ONNX.'	)


if __name__ == "__main__":
      UpperCamelCase			:       List[str]									=				argparse.ArgumentParser()
      parser.add_argument("--saved_model_path", help="Path of the saved model to check (the .pb file).")
      parser.add_argument(
          "--opset", default=1_2, 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)"
      )
      UpperCamelCase			:       str									=				parser.parse_args()

      if args.framework == "onnx":
            onnx_compliancy(args.saved_model_path, args.strict, args.opset)



