




from __future__ import annotations

import math







def lowerCamelCase__       (      _lowercase				):

     '''simple docstring'''


     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(_lowercase				) + 1				)			,						6				):
          if number % i == 0 or number % (i + 2) == 0:
               return False
     return True


__a          =			[num for num in range(3, 100_001, 2) if not is_prime(num)]







def lowerCamelCase__       (      _lowercase				):

     '''simple docstring'''


     if not isinstance(_lowercase			,						_lowercase				):
          raise ValueError('''n must be an integer'''				)
     if n <= 0:
          raise ValueError('''n must be >= 0'''				)

     UpperCAmelCase_      :							List[str]       =      []
     for num in range(len(_lowercase				)				):
          UpperCAmelCase_      :							List[str]       =      0
          while 2 * i * i <= odd_composites[num]:
               UpperCAmelCase_      :							Tuple       =      odd_composites[num] - 2 * i * i
               if is_prime(_lowercase				):
                    break
               i += 1
          else:
               list_nums.append(odd_composites[num]				)
               if len(_lowercase				) == n:
                    return list_nums

     return []







def lowerCamelCase__       (      ):

     '''simple docstring'''


     return compute_nums(1				)[0]


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
)
__a          =			logging.getLogger(__name__)

if __name__ == "__main__":
     __a          =			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=30_522, type=int)
     __a          =			parser.parse_args()

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

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