





def 					lowerCAmelCase_			(	__a		)					->		list:







  """simple docstring"""





  if len(__a		) < 2:
    return collection

  def circle_sort_util(__a     ,   __a     ,   __a		) -> bool:
    lowerCamelCase__:				str        =False

    if low == high:
      return swapped

    lowerCamelCase__:				Optional[int]        =low
    lowerCamelCase__:				Optional[Any]        =high

    while left < right:
      if collection[left] > collection[right]:
        lowerCamelCase__  , lowerCamelCase__:				List[Any]        =(
            collection[right],
            collection[left],
        )
        lowerCamelCase__:				List[str]        =True

      left += 1
      right -= 1

    if left == right and collection[left] > collection[right + 1]:
      lowerCamelCase__  , lowerCamelCase__:				Union[str, Any]        =(
          collection[right + 1],
          collection[left],
      )

      lowerCamelCase__:				List[str]        =True

    lowerCamelCase__:				Tuple        =low + int((high - low) / 2		)
    lowerCamelCase__:				int        =circle_sort_util(__a     ,   __a     ,   __a		)
    lowerCamelCase__:				int        =circle_sort_util(__a     ,   mid + 1     ,   __a		)

    return swapped or left_swap or right_swap

  lowerCamelCase__:				Any        =True

  while is_not_sorted is True:
    lowerCamelCase__:				Optional[int]        =circle_sort_util(__a     ,   0     ,   len(__a		) - 1		)

  return collection


if __name__ == "__main__":
     __A     =    input("Enter numbers separated by a comma:\n").strip()
     __A     =    [int(item) for item in user_input.split(",")]
     print(circle_sort(unsorted))








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)

