






from collections.abc import Sequence







def 						A__  (					__A   , __A = False	):







    '''simple docstring'''







    if not arr:
        return 0

    _lowerCamelCase     :		Tuple 						=						0 if allow_empty_subarrays else float("""-inf"""	)
    _lowerCamelCase     :		Tuple 						=						0.0
    for num in arr:
        _lowerCamelCase     :		int 						=						max(0 if allow_empty_subarrays else num   , curr_sum + num	)
        _lowerCamelCase     :		List[Any] 						=						max(__UpperCAmelCase   , __UpperCAmelCase	)

    return max_sum


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

    testmod()

    lowerCAmelCase			:							int     =[-2, 1, -3, 4, -1, 2, 1, -5, 4]
    print(F"""{max_subarray_sum(nums) = }""")





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""")




