






"""simple docstring"""






import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser



def       _A    (__a							)				-> Optional[int]:
				"""simple docstring"""






				SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	{}
				SCREAMING_SNAKE_CASE_   :						List[Any]							=	tokenizer(example['''content''']					,       truncation=__a							)['''input_ids''']
				SCREAMING_SNAKE_CASE_   :						List[Any]							=	len(example['''content''']							) / len(output['''input_ids''']							)
				return output


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

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

UpperCAmelCase_     :				Dict         =				time.time()
UpperCAmelCase_     :				Dict         =				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''')

UpperCAmelCase_     :				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 __future__ import annotations



def       _A    (__a					,       __a					,       __a							)				-> int | float:
    """simple docstring"""






    if len(__a							) == 0:
        raise ValueError('''find_max() arg is an empty sequence'''							)
    if (
        left >= len(__a							)
        or left < -len(__a							)
        or right >= len(__a							)
        or right < -len(__a							)
    ):
        raise IndexError('''list index out of range'''							)
    if left == right:
        return nums[left]
    SCREAMING_SNAKE_CASE_   :						str							=	(left + right) >> 1  # the middle
    SCREAMING_SNAKE_CASE_   :						int							=	find_max(__a					,       __a					,       __a							)  # find max in range[left, mid]
    SCREAMING_SNAKE_CASE_   :						str							=	find_max(__a					,       mid + 1					,       __a							)  # find max in range[mid + 1, right]

    return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
  import doctest

  doctest.testmod(verbose=True)


