





"""simple docstring"""





import argparse

import torch

from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging


logging.set_verbosity_info()
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->List[str]:





  """simple docstring"""


  lowerCAmelCase__     :int											=				BertConfig.from_json_file(_SCREAMING_SNAKE_CASE     )
  print(F"Building PyTorch model from configuration: {config}"     )
  lowerCAmelCase__     :Union[str, Any]											=				BertForPreTraining(_SCREAMING_SNAKE_CASE     )

  # Load weights from tf checkpoint
  load_tf_weights_in_bert(_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     )


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(
      """--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											=						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	,  _SCREAMING_SNAKE_CASE     )   ->list[str]:





  """simple docstring"""


  return [sentence[i : i + ngram_size] for i in range(len(_SCREAMING_SNAKE_CASE     ) - ngram_size + 1     )]


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

  testmod()
