

"""simple docstring"""



import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()





def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case,      snake_case):
     # Initialise PyTorch model
     __snake_case				=							TaConfig.from_json_file(snake_case)
     print(f"Building PyTorch model from configuration: {config}")
     __snake_case				=							TaForConditionalGeneration(snake_case)

     # Load weights from tf checkpoint
     load_tf_weights_in_ta(snake_case,      snake_case,      snake_case)

     # Save pytorch-model
     print(f"Save PyTorch model to {pytorch_dump_path}")
     model.save_pretrained(snake_case)


if __name__ == "__main__":
       __lowercase		:		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(
           "--config_file",
           default=None,
           type=str,
           required=True,
           help=(
               "The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture."
           ),
       )
       parser.add_argument(
           "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
       )
       __lowercase		:		int														=							parser.parse_args()
       convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)
"""simple docstring"""



import re





def    SCREAMING_SNAKE_CASE       (     snake_case):
     return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''',      str_)]





def    SCREAMING_SNAKE_CASE       (     snake_case):
     __snake_case				=							split_input(str_)
     return "".join(
         [''''''.join([char.capitalize() for char in sub_str]) for sub_str in string_split])





def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case,      snake_case):
     try:
          __snake_case				=							split_input(snake_case)
          if upper:
               __snake_case				=							''''''.join(
                   [
                       separator.join([char.upper() for char in sub_str])
                       for sub_str in string_split
                   ])
          else:
               __snake_case				=							''''''.join(
                   [
                       separator.join([char.lower() for char in sub_str])
                       for sub_str in string_split
                   ])
          return res_str
     except IndexError:
          return "not valid string"





def    SCREAMING_SNAKE_CASE       (     snake_case):
     return to_simple_case(snake_case)





def    SCREAMING_SNAKE_CASE       (     snake_case):
     try:
          __snake_case				=							to_simple_case(snake_case)
          return res_str[0].lower() + res_str[1:]
     except IndexError:
          return "not valid string"





def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
     return to_complex_case(snake_case,      snake_case,      '''_''')





def    SCREAMING_SNAKE_CASE       (     snake_case,      snake_case):
     return to_complex_case(snake_case,      snake_case,      '''-''')


if __name__ == "__main__":
       __import__("doctest").testmod()