




def     __magic_name__       (				A	:      List[Any]     ):






			'''simple docstring'''







			stooge(a_,						0,						len(a_     ) - 1     )
			return arr




def     __magic_name__       (				A	:      Any,						A	:      str,						A	:      List[Any]     ):






			'''simple docstring'''







			if i >= h:
						return

			# If first element is smaller than the last then swap them
			if arr[i] > arr[h]:
						a					=    arr[h], arr[i]

			# If there are more than 2 elements in the array
			if h - i + 1 > 2:
						a					=    (int)((h - i + 1) / 3     )

						# Recursively sort first 2/3 elements
						stooge(a_,						a_,						(h - t)     )

						# Recursively sort last 2/3 elements
						stooge(a_,						i + t,						(a_)     )

						# Recursively sort first 2/3 elements
						stooge(a_,						a_,						(h - t)     )


if __name__ == "__main__":
		__lowerCAmelCase	:       Any     =	input('Enter numbers separated by a comma:\n').strip()
		__lowerCAmelCase	:       Union[str, Any]     =	[int(item) for item in user_input.split(',')]
		print(stooge_sort(unsorted))












import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser




def     __magic_name__       (				A	:      List[str]     ):






			'''simple docstring'''







			a					=    {}
			a					=    tokenizer(example["content"],						truncation=A     )["input_ids"]
			a					=    len(example["content"]     ) / len(output["input_ids"]     )
			return output


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

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

__lowerCAmelCase	:       int     =	time.time()
__lowerCAmelCase	:       Optional[int]     =	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''')






