
"""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     (		__lowerCamelCase,		__lowerCamelCase,		__lowerCamelCase  ):
   # Initialise PyTorch model
   UpperCAmelCase_					:					List[Any]			     =    AlbertConfig.from_json_file(__lowerCamelCase  )
   print(f"""Building PyTorch model from configuration: {config}"""  )
   UpperCAmelCase_					:					Union[str, 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__":
    _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(
        '--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.'
    )
    _a		       =							parser.parse_args()
    convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)



from math import ceil
def       A	(    _lowercase = 1_001						):
						SCREAMING_SNAKE_CASE							:    Any							=							1

						for i in range(1		,  int(ceil(n / 2.0						)						)						):
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							2 * i + 1
												SCREAMING_SNAKE_CASE							:    int							=							2 * i
												SCREAMING_SNAKE_CASE							:    List[str]							=							total + 4 * odd**2 - 6 * even

						return total


if __name__ == "__main__":
					import sys

					if len(sys.argv) == 1:
										print(solution())
					else:
										try:
															__UpperCamelCase		:       Dict									=     int(sys.argv[1])
															print(solution(n))
										except ValueError:
															print('Invalid entry - please enter a number')





