


'''simple docstring'''

import argparse

import torch

from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert


logging.set_verbosity_info()
def      __a	(							A__						,       A__						,       A__       )						->			Dict:
  lowerCAmelCase											=	AlbertConfig.from_json_file(UpperCamelCase__       )
  print(f"Building PyTorch model from configuration: {config}"       )
  lowerCAmelCase											=	AlbertForPreTraining(UpperCamelCase__       )

  # Load weights from tf checkpoint
  load_tf_weights_in_albert(UpperCamelCase__						,       UpperCamelCase__						,       UpperCamelCase__       )

  # Save pytorch-model
  print(f"Save PyTorch model to {pytorch_dump_path}"       )
  torch.save(model.state_dict()						,       UpperCamelCase__       )


if __name__ == "__main__":
       lowercase   :						Tuple								=			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(
           '--albert_config_file',
           default=None,
           type=str,
           required=True,
           help=(
               'The config json file corresponding to the pre-trained ALBERT 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.'
       )
       lowercase   :						Tuple								=			parser.parse_args()
       convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)






"""simple docstring"""

def lowerCAmelCase_   (					UpperCamelCase__						:			list					, UpperCamelCase__						:			int					, UpperCamelCase__						:			int = 0					, UpperCamelCase__						:			int = 0			):






 """simple docstring"""







 __lowercase						=						right or len(UpperCamelCase__			) - 1
 if left > right:
  return -1
 elif list_data[left] == key:
  return left
 elif list_data[right] == key:
  return right
 else:
  return search(UpperCamelCase__					, UpperCamelCase__					, left + 1					, right - 1			)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
