





import argparse

import torch

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


logging.set_verbosity_info()






def    _A	(   lowerCamelCase				,			lowerCamelCase				,			lowerCamelCase ):
   # Initialise PyTorch model
   a__						:    Any   		=	AlbertConfig.from_json_file(lowerCamelCase )
   print(F"""Building PyTorch model from configuration: {config}""" )
   a__						:    Any   		=	AlbertForPreTraining(lowerCamelCase )

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

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


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE__							:      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(
      """--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."""
  )
  SCREAMING_SNAKE_CASE__							:      Union[str, Any]         =    parser.parse_args()
  convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)








def    _A	(   lowerCamelCase = 200 ):
   a__						:    List[str]   		=	[1, 2, 5, 10, 20, 50, 100, 200]
   a__						:    Dict   		=	[0] * (pence + 1)
   a__						:    int   		=	1  # base case: 1 way to make 0 pence

   for coin in coins:
      for i in range(lowerCamelCase				,			pence + 1				,			1 ):
         number_of_ways[i] += number_of_ways[i - coin]
   return number_of_ways[pence]


if __name__ == "__main__":
  assert solution(2_0_0) == 7_3_6_8_2

