
"""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						(    snake_case				:List[str]    , snake_case				:Any    , snake_case				:int		)				->     List[Any]:
 __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     :    int       =			parser.parse_args()
      convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)





"""simple docstring"""

from math import isqrt






def 							A						(    snake_case				:int		)				->     list[int]:
 __UpperCamelCase      =	[True] * max_number
 for i in range(2    , isqrt(max_number - 1		) + 1		):
  if is_prime[i]:
   for j in range(i**2    , snake_case    , snake_case		):
    __UpperCamelCase      =	False

 return [i for i in range(2    , snake_case		) if is_prime[i]]






def 							A						(    snake_case				:int = 1_0**8		)				->     int:
 __UpperCamelCase      =	calculate_prime_numbers(max_number // 2		)

 __UpperCamelCase      =	0
 __UpperCamelCase      =	0
 __UpperCamelCase      =	len(snake_case		) - 1
 while left <= right:
  while prime_numbers[left] * prime_numbers[right] >= max_number:
   right -= 1
  semiprimes_count += right - left + 1
  left += 1

 return semiprimes_count


if __name__ == "__main__":
      print(f'''{solution() = }''')



