


'''simple docstring'''






import itertools
import math


def    _snake_case  (	A			)		->       bool:

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5					,       int(math.sqrt(A			) + 1			)					,       6			):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True


def    _snake_case  (	)		->       Optional[int]:
							lowerCAmelCase__			  =      2
							while True:
														if is_prime(A			):
																					yield num
														num += 1


def    _snake_case  (	A = 10001			)		->       int:
							return next(itertools.islice(prime_generator()					,       nth - 1					,       A			)			)


if __name__ == "__main__":
		print(f"""{solution() = }""")






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
)
_lowerCamelCase 					=      logging.getLogger(__name__)

if __name__ == "__main__":
	_lowerCamelCase 					=      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=30522, type=int)
	_lowerCamelCase 					=      parser.parse_args()

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

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