






"""simple docstring"""






def 					_A			(__a							) ->       str:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_      :  Dict    						=		0
    SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		len(__a							)

    for i in range(n - 1							):
        for j in range(i + 1    ,				__a							):
            if arr[i] > arr[j]:
                num_inversions += 1

    return num_inversions



def 					_A			(__a							) ->       int:
    """simple docstring"""






    if len(__a							) <= 1:
        return arr, 0
    SCREAMING_SNAKE_CASE_      :  int    						=		len(__a							) // 2
    SCREAMING_SNAKE_CASE_      :  Tuple    						=		arr[0:mid]
    SCREAMING_SNAKE_CASE_      :  List[str]    						=		arr[mid:]

    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  List[str]    						=		count_inversions_recursive(__a							)
    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		count_inversions_recursive(__a							)
    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  Tuple    						=		_count_cross_inversions(__a    ,				__a							)

    SCREAMING_SNAKE_CASE_      :  str    						=		inversion_p + inversions_q + cross_inversions
    return c, num_inversions



def 					_A			(__a    ,				__a							) ->       Dict:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_      :  Tuple    						=		[]
    SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		0
    while i < len(__a							) and j < len(__a							):
        if p[i] > q[j]:
            # if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
            # These are all inversions. The claim emerges from the
            # property that P is sorted.
            num_inversion += len(__a							) - i
            r.append(q[j]							)
            j += 1
        else:
            r.append(p[i]							)
            i += 1

    if i < len(__a							):
        r.extend(p[i:]							)
    else:
        r.extend(q[j:]							)

    return r, num_inversion



def 					_A			() ->       int:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_      :  Dict    						=		[10, 2, 1, 5, 5, 2, 11]

    # this arr has 8 inversions:
    # (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

    SCREAMING_SNAKE_CASE_      :  Dict    						=		count_inversions_bf(__a							)
    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  List[str]    						=		count_inversions_recursive(__a							)

    assert num_inversions_bf == num_inversions_recursive == 8

    print('''number of inversions = '''    ,				__a							)

    # testing an array with zero inversion (a sorted arr_1)

    arr_a.sort()
    SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		count_inversions_bf(__a							)
    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  int    						=		count_inversions_recursive(__a							)

    assert num_inversions_bf == num_inversions_recursive == 0
    print('''number of inversions = '''    ,				__a							)

    # an empty list should also have zero inversions
    SCREAMING_SNAKE_CASE_      :  int    						=		[]
    SCREAMING_SNAKE_CASE_      :  Tuple    						=		count_inversions_bf(__a							)
    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		count_inversions_recursive(__a							)

    assert num_inversions_bf == num_inversions_recursive == 0
    print('''number of inversions = '''    ,				__a							)


if __name__ == "__main__":
  main()










"""simple docstring"""






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
)
UpperCAmelCase_   : Dict   			= logging.getLogger(__name__)

if __name__ == "__main__":
  UpperCAmelCase_   : List[str]   			= 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)
  UpperCAmelCase_   : Optional[Any]   			= parser.parse_args()

  logger.info(f'''Loading data from {args.data_file}''')
  with open(args.data_file, """rb""") as fp:
    UpperCAmelCase_   : Union[str, Any]   			= pickle.load(fp)

  logger.info("""Counting occurrences for MLM.""")
  UpperCAmelCase_   : Any   			= Counter()
  for tk_ids in data:
    counter.update(tk_ids)
  UpperCAmelCase_   : List[Any]   			= [0] * args.vocab_size
  for k, v in counter.items():
    UpperCAmelCase_   : Dict   			= 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)


