






'''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        __SCREAMING_SNAKE_CASE (     _a			):
 snake_case_												=							"""speech_to_text_2"""
 snake_case_												=							["""past_key_values"""]
 snake_case_												=							{"""num_attention_heads""": """decoder_attention_heads""", """hidden_size""": """d_model"""}




 def __init__( self		:							List[str]   , __lowercase		:							str=1_00_00   , __lowercase		:							List[Any]=6   , __lowercase		:							str=20_48   , __lowercase		:							List[str]=4   , __lowercase		:							Optional[Any]=0.0   , __lowercase		:							List[Any]=True   , __lowercase		:							Union[str, Any]="relu"   , __lowercase		:							List[Any]=2_56   , __lowercase		:							Optional[Any]=0.1   , __lowercase		:							Optional[int]=0.0   , __lowercase		:							Tuple=0.0   , __lowercase		:							Dict=0.02   , __lowercase		:							Optional[Any]=2   , __lowercase		:							Dict=True   , __lowercase		:							Any=1   , __lowercase		:							List[Any]=0   , __lowercase		:							Optional[Any]=2   , __lowercase		:							Optional[int]=10_24   , **__lowercase		:							Dict   , )		->  Any:
       SCREAMING_SNAKE_CASE__       :			int													=vocab_size
       SCREAMING_SNAKE_CASE__       :			Tuple													=d_model
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=decoder_ffn_dim
       SCREAMING_SNAKE_CASE__       :			int													=decoder_layers
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=decoder_attention_heads
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=dropout
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=attention_dropout
       SCREAMING_SNAKE_CASE__       :			str													=activation_dropout
       SCREAMING_SNAKE_CASE__       :			Dict													=activation_function
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=init_std
       SCREAMING_SNAKE_CASE__       :			Dict													=decoder_layerdrop
       SCREAMING_SNAKE_CASE__       :			Any													=use_cache
       SCREAMING_SNAKE_CASE__       :			str													=decoder_layers
       SCREAMING_SNAKE_CASE__       :			Any													=scale_embedding  # scale factor will be sqrt(d_model) if True
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=max_target_positions

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







'''simple docstring'''
import math





def 	_a(					UpperCamelCase__			:  int							):




      '''simple docstring'''






      return math.sqrt(UpperCamelCase__							) * math.sqrt(UpperCamelCase__							) == num





def 	_a(					UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[Any]													=0
      SCREAMING_SNAKE_CASE__       :			Any													=n
      while left <= right:
            SCREAMING_SNAKE_CASE__       :			str													=(left + right) // 2
            if mid**2 == n:
                  return True
            elif mid**2 > n:
                  SCREAMING_SNAKE_CASE__       :			Optional[Any]													=mid - 1
            else:
                  SCREAMING_SNAKE_CASE__       :			Tuple													=mid + 1
      return False


if __name__ == "__main__":
  import doctest

  doctest.testmod()