

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   List[str]      ):



     '''simple docstring'''





     lowercase__   :       Any				=	0
     lowercase__   :       List[Any]				=	len(SCREAMING_SNAKE_CASE_      )

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

     return num_inversions

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Optional[int]      ):



     '''simple docstring'''





     if len(SCREAMING_SNAKE_CASE_      ) <= 1:
          return arr, 0
     lowercase__   :       Optional[Any]				=	len(SCREAMING_SNAKE_CASE_      ) // 2
     lowercase__   :       List[Any]				=	arr[0:mid]
     lowercase__   :       str				=	arr[mid:]

     lowercase__				,			lowercase__   :       Any				=	count_inversions_recursive(SCREAMING_SNAKE_CASE_      )
     lowercase__				,			lowercase__   :       List[Any]				=	count_inversions_recursive(SCREAMING_SNAKE_CASE_      )
     lowercase__				,			lowercase__   :       str				=	_count_cross_inversions(SCREAMING_SNAKE_CASE_     ,					SCREAMING_SNAKE_CASE_      )

     lowercase__   :       List[Any]				=	inversion_p + inversions_q + cross_inversions
     return c, num_inversions

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   int     ,					SCREAMING_SNAKE_CASE_		:   str      ):



     '''simple docstring'''





     lowercase__   :       Optional[int]				=	[]
     lowercase__   :       Optional[Any]				=	0
     while i < len(SCREAMING_SNAKE_CASE_      ) and j < len(SCREAMING_SNAKE_CASE_      ):
          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(SCREAMING_SNAKE_CASE_      ) - i
               r.append(q[j]      )
               j += 1
          else:
               r.append(p[i]      )
               i += 1

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

     return r, num_inversion

def      snake_case__      (   ):



     '''simple docstring'''





     lowercase__   :       int				=	[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)

     lowercase__   :       Any				=	count_inversions_bf(SCREAMING_SNAKE_CASE_      )
     lowercase__				,			lowercase__   :       Optional[int]				=	count_inversions_recursive(SCREAMING_SNAKE_CASE_      )

     assert num_inversions_bf == num_inversions_recursive == 8

     print('number of inversions = '     ,					SCREAMING_SNAKE_CASE_      )

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

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

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

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

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


if __name__ == "__main__":
       main()




from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case_        =			logging.get_logger(__name__)

snake_case_        =			{
    '''facebook/s2t-wav2vec2-large-en-de''': (
        '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'''
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}


class 				SCREAMING_SNAKE_CASE__ (__snake_case					):
    __lowerCamelCase						:	List[Any]														=					"""speech_to_text_2"""
    __lowerCamelCase						:	str														=					["""past_key_values"""]
    __lowerCamelCase						:	List[Any]														=					{"""num_attention_heads""": """decoder_attention_heads""", """hidden_size""": """d_model"""}





    def __init__(				self						,       a=1_0000						,       a=6						,       a=2048						,       a=4						,       a=0.0						,       a=True						,       a="relu"						,       a=256						,       a=0.1						,       a=0.0						,       a=0.0						,       a=0.02						,       a=2						,       a=True						,       a=1						,       a=0						,       a=2						,       a=1024						,       **a						,       ):
         lowercase__   :       Optional[int]				=	vocab_size
         lowercase__   :       List[str]				=	d_model
         lowercase__   :       int				=	decoder_ffn_dim
         lowercase__   :       Optional[Any]				=	decoder_layers
         lowercase__   :       int				=	decoder_attention_heads
         lowercase__   :       Dict				=	dropout
         lowercase__   :       Optional[int]				=	attention_dropout
         lowercase__   :       Optional[int]				=	activation_dropout
         lowercase__   :       Optional[int]				=	activation_function
         lowercase__   :       Dict				=	init_std
         lowercase__   :       List[Any]				=	decoder_layerdrop
         lowercase__   :       int				=	use_cache
         lowercase__   :       Any				=	decoder_layers
         lowercase__   :       Optional[int]				=	scale_embedding  # scale factor will be sqrt(d_model) if True
         lowercase__   :       Tuple				=	max_target_positions

         super().__init__(
             pad_token_id=a						,       bos_token_id=a						,       eos_token_id=a						,       decoder_start_token_id=a						,       **a						,       )

