






import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser




def 				A		(					lowercase__  :  Optional[int]  )		-> Optional[Any]:
	UpperCamelCase__ :Union[str, Any]						=      {}
	UpperCamelCase__ :Optional[int]						=      tokenizer(example["""content"""] ,		truncation=lowercase__  )["""input_ids"""]
	UpperCamelCase__ :int						=      len(example["""content"""]  ) / len(output["""input_ids"""]  )
	return output


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

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

UpperCamelCase        =				time.time()
UpperCamelCase        =				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        =				time.time()
ds.push_to_hub(args.tokenized_data_repo)




print(f'''Data pushed to the hub in {time.time()-t_start:.2f}s''')

def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	list[int]		,   SCREAMING_SNAKE_CASE_	:	int       )  ->     bool:
						_lowercase					       =					len(SCREAMING_SNAKE_CASE_       )
						_lowercase					       =					[[False] * (required_sum + 1) for _ in range(arr_len + 1       )]

						# for each arr value, a sum of zero(0) can be formed by not taking any element
						# hence True/1
						for i in range(arr_len + 1       ):
												_lowercase					       =					True

						# sum is not zero and set is empty then false
						for i in range(1		,   required_sum + 1       ):
												_lowercase					       =					False

						for i in range(1		,   arr_len + 1       ):
												for j in range(1		,   required_sum + 1       ):
																		if arr[i - 1] > j:
																								_lowercase					       =					subset[i - 1][j]
																		if arr[i - 1] <= j:
																								_lowercase					       =					subset[i - 1][j] or subset[i - 1][j - arr[i - 1]]

						return subset[arr_len][required_sum]


if __name__ == "__main__":
		import doctest

		doctest.testmod()