import argparse

import torch

from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging


logging.set_verbosity_info()




def       __lowerCAmelCase      (						A_   : Dict						,	A_   : Union[str, Any]						,	A_   : List[str]					)    ->  Dict:
  __UpperCAmelCase						    =       RemBertConfig.from_json_file(A_					)
  print("Building PyTorch model from configuration: {}".format(str(A_					)					)					)
  __UpperCAmelCase						    =       RemBertModel(A_					)

  # Load weights from tf checkpoint
  load_tf_weights_in_rembert(A_						,	A_						,	A_					)

  # Save pytorch-model
  print("Save PyTorch model to {}".format(A_					)					)
  torch.save(model.state_dict()						,	A_					)


if __name__ == "__main__":
       a_							=      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(
           """--rembert_config_file""",
           default=None,
           type=str,
           required=True,
           help=(
               """The config json file corresponding to the pre-trained RemBERT 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_							=      parser.parse_args()
       convert_rembert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.rembert_config_file, args.pytorch_dump_path)




import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union


@dataclass
class 			UpperCAmelCase__    :



  """simple docstring"""






  lowerCAmelCase__		:	Optional[Union[str, Path]]    		= None
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	Optional[Dict]    		= None
  lowerCAmelCase__		:	Optional[str]    		= None
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	bool    		= True
  lowerCAmelCase__		:	Optional[int]    		= None
  lowerCAmelCase__		:	int    		= 1
  lowerCAmelCase__		:	Optional[Union[str, bool]]    		= None
  lowerCAmelCase__		:	bool    		= False
  lowerCAmelCase__		:	Optional[Dict]    		= None
  lowerCAmelCase__		:	Optional[str]    		= None






  def 	_UpperCAmelCase				(				self:			Any   ) -> "DownloadConfig":




    '''simple docstring'''




    return self.__class__(**{k: copy.deepcopy(__lowerCAmelCase   ) for k, v in self.__dict__.items()}   )



