





'''simple docstring'''






import argparse

import torch

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


logging.set_verbosity_info()





def    lowercase_   (		lowercase__					,	lowercase__					,	lowercase__    ) ->List[str]:
						# Initialise PyTorch model
						_snake_case: Union[str, Any]	       =		RoFormerConfig.from_json_file(a_    )
						print(F'''Building PyTorch model from configuration: {config}'''    )
						_snake_case: str	       =		RoFormerForMaskedLM(a_    )

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

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


if __name__ == "__main__":
		A :			Union[str, Any]							   =      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.'
		)
		A :			List[str]							   =      parser.parse_args()
		convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)







"""simple docstring"""







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


SCREAMING_SNAKE_CASE_  					= logging.get_logger(__name__)






class      __a      (       lowerCAmelCase_      ):







       def __init__(       self				,*lowerCamelCase_				,**lowerCamelCase_		):



          '''simple docstring'''

          warnings.warn(
              "The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
              " Please use MobileNetV1ImageProcessor instead."				,lowerCamelCase_				,)
          super().__init__(*lowerCamelCase_				,**lowerCamelCase_		)

