


'''simple docstring'''
import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser


def 			a      (			__a   )  ->	List[Any]:



					'''simple docstring'''






					UpperCamelCase__   :Union[str, Any]												= {}
					UpperCamelCase__   :str												= tokenizer(example['''content'''] ,					truncation=__a   )['''input_ids''']
					UpperCamelCase__   :str												= len(example['''content''']   ) / len(output['''input_ids''']   )
					return output


__snake_case							      =     HfArgumentParser(PretokenizationArguments)
__snake_case							      =     parser.parse_args()
if args.num_workers is None:
		__snake_case							      =     multiprocessing.cpu_count()
__snake_case							      =     AutoTokenizer.from_pretrained(args.tokenizer_dir)

__snake_case							      =     time.time()
__snake_case							      =     load_dataset(args.dataset_name, split='''train''')
print(F"""Dataset loaded in {time.time()-t_start:.2f}s""")

__snake_case							      =     time.time()
__snake_case							      =     ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        '''repo_name''',
        '''path''',
        '''copies''',
        '''size''',
        '''content''',
        '''license''',
        '''hash''',
        '''line_mean''',
        '''line_max''',
        '''alpha_frac''',
        '''autogenerated''',
    ],
)
print(F"""Dataset tokenized in {time.time()-t_start:.2f}s""")

__snake_case							      =     time.time()
ds.push_to_hub(args.tokenized_data_repo)







print(F"""Data pushed to the hub in {time.time()-t_start:.2f}s""")


def      a      (			A__	:   str      ,   A__	:   bool = False     )    ->      str:





      """simple docstring"""



      if not isinstance(A__      ,   A__     ):
            _lowercase	       =F'''Expected string as input, found {type(A__     )}'''
            raise ValueError(A__     )
      if not isinstance(A__      ,   A__     ):
            _lowercase	       =F'''Expected boolean as use_pascal parameter, found {type(A__     )}'''
            raise ValueError(A__     )

      _lowercase	       =input_str.split('_'     )

      _lowercase	       =0 if use_pascal else 1

      _lowercase	       =words[start_index:]

      _lowercase	       =[word[0].upper() + word[1:] for word in words_to_capitalize]

      _lowercase	       ='' if use_pascal else words[0]

      return "".join([initial_word, *capitalized_words]     )


if __name__ == "__main__":
  from doctest import testmod

  testmod()


