




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
lowerCamelCase							:						Union[str, Any]					       =  "."

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

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Union[str, Any]      ,				lowercase      :			Union[str, Any]      ,				lowercase      :			Union[str, Any]	):


      '''simple docstring'''



      lowerCamelCase_							=       SavedModel()
      lowerCamelCase_							=       []

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

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

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

      lowerCamelCase_							=       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
      lowerCamelCase_							=       sorted(lowercase	)
      lowerCamelCase_							=       []

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

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


if __name__ == "__main__":
 lowerCamelCase							:						Tuple					       =  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)"
 )
 lowerCamelCase							:						Optional[Any]					       =  parser.parse_args()

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











def 		lowercase__  (				_UpperCamelCase) ->			list:
      """simple docstring"""

      if bit_count < 0:
            raise ValueError('The given input must be positive')

      # get the generated string sequence
      UpperCamelCase					       =  gray_code_sequence_string(_UpperCamelCase)
      #
      # convert them to integers
      for i in range(len(_UpperCamelCase)):
            UpperCamelCase					       =  int(sequence[i]       ,							2)

      return sequence
def 		lowercase__  (				_UpperCamelCase) ->			list:
      """simple docstring"""

      if bit_count == 0:
            return ["0"]

      if bit_count == 1:
            return ["0", "1"]

      UpperCamelCase					       =  1 << bit_count  # defines the length of the sequence
      # 1<< n is equivalent to 2^n

      # recursive answer will generate answer for n-1 bits
      UpperCamelCase					       =  gray_code_sequence_string(bit_count - 1)

      UpperCamelCase					       =  []

      # append 0 to first half of the smaller sequence generated
      for i in range(seq_len // 2):
            UpperCamelCase					       =  '0' + smaller_sequence[i]
            sequence.append(_UpperCamelCase)

      # append 1 to second half ... start from the end of the list
      for i in reversed(range(seq_len // 2)):
            UpperCamelCase					       =  '1' + smaller_sequence[i]
            sequence.append(_UpperCamelCase)

      return sequence


if __name__ == "__main__":
       import doctest

       doctest.testmod()



