





def 					lowerCAmelCase_			(	)					->		List[str]:







  """simple docstring"""





  lowerCamelCase__:				int        =[31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]

  lowerCamelCase__:				Optional[Any]        =6
  lowerCamelCase__:				List[str]        =1
  lowerCamelCase__:				Dict        =1901

  lowerCamelCase__:				Any        =0

  while year < 2001:
    day += 7

    if (year % 4 == 0 and year % 100 != 0) or (year % 400 == 0):
      if day > days_per_month[month - 1] and month != 2:
        month += 1
        lowerCamelCase__:				int        =day - days_per_month[month - 2]
      elif day > 29 and month == 2:
        month += 1
        lowerCamelCase__:				int        =day - 29
    else:
      if day > days_per_month[month - 1]:
        month += 1
        lowerCamelCase__:				Dict        =day - days_per_month[month - 2]

    if month > 12:
      year += 1
      lowerCamelCase__:				Tuple        =1

    if year < 2001 and day == 1:
      sundays += 1
  return sundays


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
)
__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=3_0522, 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)

