






def 						A__  (					__A	):







    '''simple docstring'''
    _lowerCamelCase     :		List[str] 						=						0

    # if input_string is "aba" than new_input_string become "a|b|a"
    _lowerCamelCase     :		Optional[Any] 						=						""""""
    _lowerCamelCase     :		Optional[Any] 						=						""""""

    # append each character + "|" in new_string for range(0, length-1)
    for i in input_string[: len(__A	) - 1]:
        new_input_string += i + "|"
    # append last character
    new_input_string += input_string[-1]

    # we will store the starting and ending of previous furthest ending palindromic
    # substring
    _lowerCamelCase     :		List[Any] 						=						0, 0

    # length[i] shows the length of palindromic substring with center i
    _lowerCamelCase     :		Optional[Any] 						=						[1 for i in range(len(__A	)	)]

    # for each character in new_string find corresponding palindromic string
    _lowerCamelCase     :		Optional[int] 						=						0
    for j in range(len(__A	)	):
        _lowerCamelCase     :		Union[str, Any] 						=						1 if j > r else min(length[l + r - j] // 2   , r - j + 1	)
        while (
            j - k >= 0
            and j + k < len(__A	)
            and new_input_string[k + j] == new_input_string[j - k]
        ):
            k += 1

        _lowerCamelCase     :		Dict 						=						2 * k - 1

        # does this string is ending after the previously explored end (that is r) ?
        # if yes the update the new r to the last index of this
        if j + k - 1 > r:
            _lowerCamelCase     :		Optional[int] 						=						j - k + 1  # noqa: E741
            _lowerCamelCase     :		List[str] 						=						j + k - 1

        # update max_length and start position
        if max_length < length[j]:
            _lowerCamelCase     :		int 						=						length[j]
            _lowerCamelCase     :		Optional[int] 						=						j

    # create that string
    _lowerCamelCase     :		Dict 						=						new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
    for i in s:
        if i != "|":
            output_string += i

    return output_string


if __name__ == "__main__":
    import doctest

    doctest.testmod()





import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser







def 						A__  (					__A	):







    '''simple docstring'''
    _lowerCamelCase     :		Tuple 						=						{}
    _lowerCamelCase     :		List[Any] 						=						tokenizer(example["""content"""]   , truncation=__A	)["""input_ids"""]
    _lowerCamelCase     :		Tuple 						=						len(example["""content"""]	) / len(output["""input_ids"""]	)
    return output


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

lowerCAmelCase			:							str     =time.time()
lowerCAmelCase			:							Union[str, Any]     =load_dataset(args.dataset_name, split="train")
print(F"""Dataset loaded in {time.time()-t_start:.2f}s""")

lowerCAmelCase			:							Dict     =time.time()
lowerCAmelCase			:							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""")

lowerCAmelCase			:							Tuple     =time.time()
ds.push_to_hub(args.tokenized_data_repo)
print(F"""Data pushed to the hub in {time.time()-t_start:.2f}s""")




