



"""simple docstring"""





import random




def 	UpperCAmelCase     (		A	:						Optional[Any]     ,				A	:						Any     ,				A	:						str       ):

		'''simple docstring'''


		_UpperCAmelCase							 =		a[left_index]
		_UpperCAmelCase							 =		left_index + 1
		for j in range(left_index + 1     ,				A       ):
				if a[j] < pivot:
						_UpperCAmelCase ,					_UpperCAmelCase							 =		a[i], a[j]
						i += 1
		_UpperCAmelCase ,					_UpperCAmelCase							 =		a[i - 1], a[left_index]
		return i - 1




def 	UpperCAmelCase     (		A	:						Dict     ,				A	:						str     ,				A	:						str       ):

		'''simple docstring'''


		if left < right:
				_UpperCAmelCase							 =		random.randint(A     ,				right - 1       )
				_UpperCAmelCase ,					_UpperCAmelCase							 =		(
				    a[left],
				    a[pivot],
				)  # switches the pivot with the left most bound
				_UpperCAmelCase							 =		partition(A     ,				A     ,				A       )
				quick_sort_random(
				    A     ,				A     ,				A       )  # recursive quicksort to the left of the pivot point
				quick_sort_random(
				    A     ,				pivot_index + 1     ,				A       )  # recursive quicksort to the right of the pivot point




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		_UpperCAmelCase							 =		input('Enter numbers separated by a comma:\n'       ).strip()
		_UpperCAmelCase							 =		[int(A       ) for item in user_input.split(','       )]

		quick_sort_random(A     ,				0     ,				len(A       )       )

		print(A       )


if __name__ == "__main__":
					main()







"""simple docstring"""





import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
lowercase  							=					logging.getLogger(__name__)

if __name__ == "__main__":
					lowercase  							=					argparse.ArgumentParser(
					    description='''Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)'''
					)
					parser.add_argument(
					    '''--data_file''', type=str, default='''data/dump.bert-base-uncased.pickle''', help='''The binarized dataset.'''
					)
					parser.add_argument(
					    '''--token_counts_dump''', type=str, default='''data/token_counts.bert-base-uncased.pickle''', help='''The dump file.'''
					)
					parser.add_argument('''--vocab_size''', default=3_05_22, type=int)
					lowercase  							=					parser.parse_args()

					logger.info(F'''Loading data from {args.data_file}''')
					with open(args.data_file, '''rb''') as fp:
										lowercase  							=					pickle.load(fp)

					logger.info('''Counting occurrences for MLM.''')
					lowercase  							=					Counter()
					for tk_ids in data:
										counter.update(tk_ids)
					lowercase  							=					[0] * args.vocab_size
					for k, v in counter.items():
										lowercase  							=					v

					logger.info(F'''Dump to {args.token_counts_dump}''')
					with open(args.token_counts_dump, '''wb''') as handle:
										pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)


