"""simple docstring"""






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


__A			   = logging.get_logger(__name__)

__A			   = {
    "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     UpperCAmelCase						(__lowercase  ):



    """simple docstring"""

    _UpperCAmelCase	:Union[str, Any]						    = '''speech_to_text_2'''
    _UpperCAmelCase	:Any						    = ['''past_key_values''']
    _UpperCAmelCase	:Optional[Any]						    = {'''num_attention_heads''': '''decoder_attention_heads''', '''hidden_size''': '''d_model'''}






    def __init__(   self    ,			_UpperCAmelCase=10000    ,			_UpperCAmelCase=6    ,			_UpperCAmelCase=2048    ,			_UpperCAmelCase=4    ,			_UpperCAmelCase=0.0    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase="relu"    ,			_UpperCAmelCase=256    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=0.0    ,			_UpperCAmelCase=0.0    ,			_UpperCAmelCase=0.02    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=1    ,			_UpperCAmelCase=0    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase=1024    ,			**_UpperCAmelCase    ,			):
       lowercase__:   Optional[Any]					=      vocab_size
       lowercase__:   List[Any]					=      d_model
       lowercase__:   Optional[int]					=      decoder_ffn_dim
       lowercase__:   Optional[int]					=      decoder_layers
       lowercase__:   Any					=      decoder_attention_heads
       lowercase__:   Tuple					=      dropout
       lowercase__:   Union[str, Any]					=      attention_dropout
       lowercase__:   List[Any]					=      activation_dropout
       lowercase__:   Union[str, Any]					=      activation_function
       lowercase__:   Dict					=      init_std
       lowercase__:   Tuple					=      decoder_layerdrop
       lowercase__:   Optional[Any]					=      use_cache
       lowercase__:   Tuple					=      decoder_layers
       lowercase__:   List[Any]					=      scale_embedding  # scale factor will be sqrt(d_model) if True
       lowercase__:   str					=      max_target_positions

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




'''simple docstring'''




def 	a_					( lowerCamelCase	:     Optional[Any]				):
   return [
       {
           0: [1, 2],
           1: [0, 2],
           2: [0, 1, 3, 5],
           3: [2, 4],
           4: [3],
           5: [2, 6, 8],
           6: [5, 7],
           7: [6, 8],
           8: [5, 7],
       },
       {
           0: [6],
           1: [9],
           2: [4, 5],
           3: [4],
           4: [2, 3],
           5: [2],
           6: [0, 7],
           7: [6],
           8: [],
           9: [1],
       },
       {
           0: [4],
           1: [6],
           2: [],
           3: [5, 6, 7],
           4: [0, 6],
           5: [3, 8, 9],
           6: [1, 3, 4, 7],
           7: [3, 6, 8, 9],
           8: [5, 7],
           9: [5, 7],
       },
       {
           0: [1, 3],
           1: [0, 2, 4],
           2: [1, 3, 4],
           3: [0, 2, 4],
           4: [1, 2, 3],
       },
   ][index]





def 	a_					( lowerCamelCase	:     dict[int, list[int]]				):
   lowerCAmelCase     =			0
   lowerCAmelCase     =			len(lowerCamelCase				)  # No of vertices in graph
   lowerCAmelCase     =			[0] * n
   lowerCAmelCase     =			[False] * n

   def dfs(lowerCamelCase	:     Tuple	, lowerCamelCase	:     str	, lowerCamelCase	:     Dict	, lowerCamelCase	:     str				):
      lowerCAmelCase     =			True
      lowerCAmelCase     =			id_
      id_ += 1
      for to in graph[at]:
         if to == parent:
            pass
         elif not visited[to]:
            dfs(lowerCamelCase	, lowerCamelCase	, lowerCamelCase	, id_				)
            lowerCAmelCase     =			min(low[at]	, low[to]				)
            if id_ <= low[to]:
               bridges.append((at, to) if at < to else (to, at)				)
         else:
            # This edge is a back edge and cannot be a bridge
            lowerCAmelCase     =			min(low[at]	, low[to]				)

   lowerCAmelCase     =			[]
   for i in range(lowerCamelCase				):
      if not visited[i]:
         dfs(lowerCamelCase	, -1	, lowerCamelCase	, id_				)
   return bridges


if __name__ == "__main__":
       import doctest

       doctest.testmod()





