




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Dict=2_8123				)  ->							str:
    UpperCAmelCase_										=					[1] * (limit + 1)

    for i in range(2	,					int(limit**0.5				) + 1				):
        sum_divs[i * i] += i
        for k in range(i + 1	,					limit // i + 1				):
            sum_divs[k * i] += k + i

    UpperCAmelCase_										=					set()
    UpperCAmelCase_										=					0

    for n in range(1	,					limit + 1				):
        if sum_divs[n] > n:
            abundants.add(__UpperCamelCase				)

        if not any((n - a in abundants) for a in abundants				):
            res += n

    return res


if __name__ == "__main__":
 print(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=3_05_22, 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)





