



from maths.prime_check import is_prime
def 		UpperCamelCase	(   snake_case__       :    int	)	->     int:
   if not isinstance(snake_case__       ,     snake_case__	):
      UpperCamelCase    :  Optional[Any]							=	F"""Input value of [number={number}] must be an integer"""
      raise TypeError(snake_case__	)
   if is_prime(snake_case__	) and is_prime(number + 2	):
      return number + 2
   else:
      return -1


if __name__ == "__main__":
    import doctest

    doctest.testmod()








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


__UpperCAmelCase          =       logging.get_logger(__name__)

__UpperCAmelCase          =       {
    '''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 				lowerCAmelCase_		(  a__							):
       UpperCAmelCase__				:					Optional[Any]        =  "speech_to_text_2"
       UpperCAmelCase__				:					List[Any]        =  ["past_key_values"]
       UpperCAmelCase__				:					Any        =  {"num_attention_heads": "decoder_attention_heads", "hidden_size": "d_model"}
       def __init__(			self,			SCREAMING_SNAKE_CASE_=1_0000,			SCREAMING_SNAKE_CASE_=6,			SCREAMING_SNAKE_CASE_=2048,			SCREAMING_SNAKE_CASE_=4,			SCREAMING_SNAKE_CASE_=0.0,			SCREAMING_SNAKE_CASE_=True,			SCREAMING_SNAKE_CASE_="relu",			SCREAMING_SNAKE_CASE_=256,			SCREAMING_SNAKE_CASE_=0.1,			SCREAMING_SNAKE_CASE_=0.0,			SCREAMING_SNAKE_CASE_=0.0,			SCREAMING_SNAKE_CASE_=0.02,			SCREAMING_SNAKE_CASE_=2,			SCREAMING_SNAKE_CASE_=True,			SCREAMING_SNAKE_CASE_=1,			SCREAMING_SNAKE_CASE_=0,			SCREAMING_SNAKE_CASE_=2,			SCREAMING_SNAKE_CASE_=1024,			**SCREAMING_SNAKE_CASE_,			)     ->		int:
          UpperCamelCase    :  Optional[int]							=	vocab_size
          UpperCamelCase    :  List[str]							=	d_model
          UpperCamelCase    :  List[str]							=	decoder_ffn_dim
          UpperCamelCase    :  Optional[Any]							=	decoder_layers
          UpperCamelCase    :  Any							=	decoder_attention_heads
          UpperCamelCase    :  Tuple							=	dropout
          UpperCamelCase    :  str							=	attention_dropout
          UpperCamelCase    :  str							=	activation_dropout
          UpperCamelCase    :  Union[str, Any]							=	activation_function
          UpperCamelCase    :  Optional[int]							=	init_std
          UpperCamelCase    :  Tuple							=	decoder_layerdrop
          UpperCamelCase    :  Dict							=	use_cache
          UpperCamelCase    :  Any							=	decoder_layers
          UpperCamelCase    :  Union[str, Any]							=	scale_embedding  # scale factor will be sqrt(d_model) if True
          UpperCamelCase    :  Union[str, Any]							=	max_target_positions

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



