
import argparse

import torch

from transformers import RoFormerConfig, RoFormerForMaskedLM, load_tf_weights_in_roformer
from transformers.utils import logging


logging.set_verbosity_info()





def        lowerCAmelCase       (				snake_case__   :      List[Any]				,					snake_case__   :      Dict				,					snake_case__   :      Union[str, Any] )->			int:
    # Initialise PyTorch model
    A_								=					RoFormerConfig.from_json_file(_SCREAMING_SNAKE_CASE )
    print(f'Building PyTorch model from configuration: {config}' )
    A_								=					RoFormerForMaskedLM(_SCREAMING_SNAKE_CASE )

    # Load weights from tf checkpoint
    load_tf_weights_in_roformer(_SCREAMING_SNAKE_CASE				,					_SCREAMING_SNAKE_CASE				,					_SCREAMING_SNAKE_CASE )

    # Save pytorch-model
    print(f'Save PyTorch model to {pytorch_dump_path}' )
    torch.save(model.state_dict()				,					_SCREAMING_SNAKE_CASE				,					_use_new_zipfile_serialization=_SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
     __magic_name__  :  Dict     			=   argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         '--tf_checkpoint_path', default=None, type=str, required=True, help='Path to the TensorFlow checkpoint path.'
     )
     parser.add_argument(
         '--bert_config_file',
         default=None,
         type=str,
         required=True,
         help=(
             'The config json file corresponding to the pre-trained BERT model. \n'
             'This specifies the model architecture.'
         ),
     )
     parser.add_argument(
         '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
     )
     __magic_name__  :  int     			=   parser.parse_args()
     convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)








'''simple docstring'''







def       _a		(						_SCREAMING_SNAKE_CASE		: int						,      _SCREAMING_SNAKE_CASE		: int	):
						return (input_a, input_a).count(0	) % 2



def       _a		(						):
						assert xor_gate(0						,      0	) == 0
						assert xor_gate(0						,      1	) == 1
						assert xor_gate(1						,      0	) == 1
						assert xor_gate(1						,      1	) == 0


if __name__ == "__main__":
						print(xor_gate(0, 0))
						print(xor_gate(0, 1))