




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
__a          =			'.'

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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							List[Any]       =      SavedModel()
     UpperCAmelCase_      :							str       =      []

     with open(os.path.join(_lowercase			,						'''utils'''			,						'''tf_ops'''			,						'''onnx.json'''				)				) as f:
          UpperCAmelCase_      :							Union[str, Any]       =      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()				)

     UpperCAmelCase_      :							Any       =      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_      :							List[str]       =      sorted(_lowercase				)
     UpperCAmelCase_      :							int       =      []

     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__":
     __a          =			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)'
     )
     __a          =			parser.parse_args()

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





from collections import defaultdict







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Optional[int]       =      first_str.lower().strip()
     UpperCAmelCase_      :							Any       =      second_str.lower().strip()

     # Remove whitespace
     UpperCAmelCase_      :							Any       =      first_str.replace(''' '''			,						''''''				)
     UpperCAmelCase_      :							int       =      second_str.replace(''' '''			,						''''''				)

     # Strings of different lengths are not anagrams
     if len(_lowercase				) != len(_lowercase				):
          return False

     # Default values for count should be 0
     UpperCAmelCase_      :							defaultdict[str, int]       =      defaultdict(_lowercase				)

     # For each character in input strings,
     # increment count in the corresponding
     for i in range(len(_lowercase				)				):
          count[first_str[i]] += 1
          count[second_str[i]] -= 1

     return all(_count == 0 for _count in count.values()				)


if __name__ == "__main__":
     from doctest import testmod

     testmod()
     __a          =			input('Enter the first string ').strip()
     __a          =			input('Enter the second string ').strip()

     __a          =			check_anagrams(input_a, input_b)
     print(F"""{input_a} and {input_b} are {"" if status else "not "}anagrams.""")