'''simple docstring'''


import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser

def   A_      (       SCREAMING_SNAKE_CASE_						)			->Optional[int]:
  lowercase_     =       {}
  lowercase_     =       tokenizer(example["""content"""] ,	truncation=UpperCAmelCase_						)['input_ids']
  lowercase_     =       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''')





'''simple docstring'''



from __future__ import annotations

A__						:   int				=    10



def      UpperCAmelCase__   (      UpperCAmelCase_       :							list[int]				)	->						list[int]:
     __lowerCamelCase  :      List[Any]														=						1
     __lowerCamelCase  :      Any														=						max(UpperCAmelCase_				)
     while placement <= max_digit:
          # declare and initialize empty buckets
          __lowerCamelCase  :      list[list]														=						[[] for _ in range(UpperCAmelCase_				)]
          # split list_of_ints between the buckets
          for i in list_of_ints:
               __lowerCamelCase  :      List[Any]														=						int((i / placement) % RADIX				)
               buckets[tmp].append(UpperCAmelCase_				)
          # put each buckets' contents into list_of_ints
          __lowerCamelCase  :      Tuple														=						0
          for b in range(UpperCAmelCase_				):
               for i in buckets[b]:
                    __lowerCamelCase  :      List[Any]														=						i
                    a += 1
        # move to next
          placement *= RADIX
     return list_of_ints


if __name__ == "__main__":
      import doctest

      doctest.testmod()






