



def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   str													=					0
				lowercase__					:   Union[str, Any]													=					len(SCREAMING_SNAKE_CASE_						)

				for i in range(n - 1						):
								for j in range(i + 1					,			SCREAMING_SNAKE_CASE_						):
												if arr[i] > arr[j]:
																num_inversions += 1

				return num_inversions


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				if len(SCREAMING_SNAKE_CASE_						) <= 1:
								return arr, 0
				lowercase__					:   Optional[Any]													=					len(SCREAMING_SNAKE_CASE_						) // 2
				lowercase__					:   Union[str, Any]													=					arr[0:mid]
				lowercase__					:   List[Any]													=					arr[mid:]

				lowercase__							,							lowercase__					:   Optional[int]													=					count_inversions_recursive(SCREAMING_SNAKE_CASE_						)
				lowercase__							,							lowercase__					:   int													=					count_inversions_recursive(SCREAMING_SNAKE_CASE_						)
				lowercase__							,							lowercase__					:   Dict													=					_count_cross_inversions(SCREAMING_SNAKE_CASE_					,			SCREAMING_SNAKE_CASE_						)

				lowercase__					:   Any													=					inversion_p + inversions_q + cross_inversions
				return c, num_inversions


def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Optional[Any]													=					[]
				lowercase__					:   Dict													=					0
				while i < len(SCREAMING_SNAKE_CASE_						) and j < len(SCREAMING_SNAKE_CASE_						):
								if p[i] > q[j]:
												# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
												# These are all inversions. The claim emerges from the
												# property that P is sorted.
												num_inversion += len(SCREAMING_SNAKE_CASE_						) - i
												r.append(q[j]						)
												j += 1
								else:
												r.append(p[i]						)
												i += 1

				if i < len(SCREAMING_SNAKE_CASE_						):
								r.extend(p[i:]						)
				else:
								r.extend(q[j:]						)

				return r, num_inversion


def  __lowerCamelCase (       ):

				"""simple docstring"""


				lowercase__					:   Tuple													=					[10, 2, 1, 5, 5, 2, 11]

				# this arr has 8 inversions:
				# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

				lowercase__					:   Optional[Any]													=					count_inversions_bf(SCREAMING_SNAKE_CASE_						)
				lowercase__							,							lowercase__					:   Optional[int]													=					count_inversions_recursive(SCREAMING_SNAKE_CASE_						)

				assert num_inversions_bf == num_inversions_recursive == 8

				print("number of inversions = "					,			SCREAMING_SNAKE_CASE_						)

				# testing an array with zero inversion (a sorted arr_1)

				arr_a.sort()
				lowercase__					:   Union[str, Any]													=					count_inversions_bf(SCREAMING_SNAKE_CASE_						)
				lowercase__							,							lowercase__					:   Optional[Any]													=					count_inversions_recursive(SCREAMING_SNAKE_CASE_						)

				assert num_inversions_bf == num_inversions_recursive == 0
				print("number of inversions = "					,			SCREAMING_SNAKE_CASE_						)

				# an empty list should also have zero inversions
				lowercase__					:   Optional[int]													=					[]
				lowercase__					:   List[str]													=					count_inversions_bf(SCREAMING_SNAKE_CASE_						)
				lowercase__							,							lowercase__					:   Optional[Any]													=					count_inversions_recursive(SCREAMING_SNAKE_CASE_						)

				assert num_inversions_bf == num_inversions_recursive == 0
				print("number of inversions = "					,			SCREAMING_SNAKE_CASE_						)


if __name__ == "__main__":
				main()











import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Optional[Any]													=					{}
				lowercase__					:   Tuple													=					tokenizer(example["content"]					,			truncation=lowerCamelCase__						)["input_ids"]
				lowercase__					:   Optional[int]													=					len(example["content"]						) / len(output["input_ids"]						)
				return output


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

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

lowerCAmelCase__					  =  time.time()
lowerCAmelCase__					  =  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__					  =  time.time()
ds.push_to_hub(args.tokenized_data_repo)
print(f'''Data pushed to the hub in {time.time()-t_start:.2f}s''')




