



"""simple docstring"""






import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser


def     _lowercase       (						__snake_case			)		->     List[Any]:
   __lowerCAmelCase   :						List[str]				= {}
   __lowerCAmelCase   :						Optional[Any]				= tokenizer(example["content"]      ,truncation=_SCREAMING_SNAKE_CASE			)["input_ids"]
   __lowerCAmelCase   :						Optional[int]				= len(example["content"]			) / len(output["input_ids"]			)
   return output


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

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

__snake_case							:     Optional[Any]   =					time.time()
__snake_case							:     Union[str, Any]   =					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							:     List[str]   =					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 ..utils import DummyObject, requires_backends



class     A__     (						metaclass=__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			['torch', 'scipy']

	def __init__(  self:	Tuple ,    *_SCREAMING_SNAKE_CASE:	Dict ,    **_SCREAMING_SNAKE_CASE:	str)       -> Union[str, Any]:

				"""simple docstring"""

				requires_backends(self ,    ["torch", "scipy"])

	@classmethod
	def 							_SCREAMING_SNAKE_CASE     (  cls:	Optional[Any] ,    *_SCREAMING_SNAKE_CASE:	Tuple ,    **_SCREAMING_SNAKE_CASE:	Optional[Any])       -> Optional[Any]:

				"""simple docstring"""

				requires_backends(cls ,    ["torch", "scipy"])







	@classmethod
	def 							_SCREAMING_SNAKE_CASE     (  cls:	int ,    *_SCREAMING_SNAKE_CASE:	List[Any] ,    **_SCREAMING_SNAKE_CASE:	Dict)       -> Union[str, Any]:

				"""simple docstring"""

				requires_backends(cls ,    ["torch", "scipy"])