
import argparse

import torch

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


logging.set_verbosity_info()


def       A       (					lowercase    ,       lowercase    ,       lowercase )   ->  Optional[Any]:
		'''simple docstring'''

		UpperCamelCase		=     AlbertConfig.from_json_file(lowercase )
		print(f'''Building PyTorch model from configuration: {config}''' )
		UpperCamelCase		=     AlbertForPreTraining(lowercase )

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

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


if __name__ == "__main__":
					_UpperCAmelCase					: 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."
					)
					_UpperCAmelCase					: Optional[int]      =       parser.parse_args()
					convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)


from decimal import Decimal, getcontext
from math import ceil, factorial


def       A       (					lowercase )   ->  str:
		'''simple docstring'''

		if not isinstance(lowercase    ,       lowercase ):
				raise TypeError('Undefined for non-integers' )
		elif precision < 1:
				raise ValueError('Undefined for non-natural numbers' )

		UpperCamelCase		=     precision
		UpperCamelCase		=     ceil(precision / 14 )
		UpperCamelCase		=     426_880 * Decimal(10_005 ).sqrt()
		UpperCamelCase		=     1
		UpperCamelCase		=     13_591_409
		UpperCamelCase		=     Decimal(lowercase )
		for k in range(1    ,       lowercase ):
				UpperCamelCase		=     factorial(6 * k ) // (factorial(3 * k ) * factorial(lowercase ) ** 3)
				linear_term += 545_140_134
				exponential_term *= -262_537_412_640_768_000
				partial_sum += Decimal(multinomial_term * linear_term ) / exponential_term
		return str(constant_term / partial_sum )[:-1]


if __name__ == "__main__":
					_UpperCAmelCase					: Dict      =       50
					print(F'''The first {n} digits of pi is: {pi(n)}''')
