

import argparse

from transformers import ConvBertConfig, ConvBertModel, TFConvBertModel, load_tf_weights_in_convbert
from transformers.utils import logging


logging.set_verbosity_info()



def   UpperCamelCase(   lowercase_     ,   lowercase_     ,   lowercase_				)      ->							Union[str, Any]:





  '''simple docstring'''





  snake_case_					= ConvBertConfig.from_json_file(lowercase_				)
  snake_case_					= ConvBertModel(lowercase_				)

  snake_case_					= load_tf_weights_in_convbert(lowercase_     ,   lowercase_     ,   lowercase_				)
  model.save_pretrained(lowercase_				)

  snake_case_					= TFConvBertModel.from_pretrained(lowercase_     ,   from_pt=lowercase_				)
  tf_model.save_pretrained(lowercase_				)


if __name__ == "__main__":
    lowerCamelCase_					  =   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(
        '''--convbert_config_file''',
        default=None,
        type=str,
        required=True,
        help=(
            '''The config json file corresponding to the pre-trained ConvBERT 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.'''
    )
    lowerCamelCase_					  =   parser.parse_args()
    convert_orig_tfa_checkpoint_to_pytorch(args.tf_checkpoint_path, args.convbert_config_file, args.pytorch_dump_path)


def   UpperCamelCase(   lowercase_     ,   lowercase_				)      ->							Union[str, Any]:





  '''simple docstring'''





  if len(str(lowercase_				)				) == 1 or len(str(lowercase_				)				) == 1:
    return a * b

  snake_case_					= max(len(str(lowercase_				)				)     ,   len(str(lowercase_				)				)				)
  snake_case_					= ma // 2

  snake_case_		,							snake_case_					= divmod(lowercase_     ,   10**ma				)
  snake_case_		,							snake_case_					= divmod(lowercase_     ,   10**ma				)

  snake_case_					= karatsuba(lowercase_     ,   lowercase_				)
  snake_case_					= karatsuba((aa + aa)     ,   (ba + ba)				)
  snake_case_					= karatsuba(lowercase_     ,   lowercase_				)

  return (z * 10 ** (2 * ma)) + ((y - z - x) * 10 ** (ma)) + (x)



def   UpperCamelCase(   )      ->							Dict:





  '''simple docstring'''





  print(karatsuba(15463     ,   23489				)				)


if __name__ == "__main__":
    main()