


'''simple docstring'''





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


__lowerCamelCase												=						logging.get_logger(__name__)

__lowerCamelCase												=						{
    '''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			(			_snake_case						):
 UpperCAmelCase				=					"speech_to_text_2"
 UpperCAmelCase				=					["past_key_values"]
 UpperCAmelCase				=					{"num_attention_heads": "decoder_attention_heads", "hidden_size": "d_model"}


 def __init__(      self							:	List[str]			,       __lowerCamelCase							:	Dict=1_0_0_0_0			,       __lowerCamelCase							:	Any=6			,       __lowerCamelCase							:	Any=2_0_4_8			,       __lowerCamelCase							:	int=4			,       __lowerCamelCase							:	int=0.0			,       __lowerCamelCase							:	List[Any]=True			,       __lowerCamelCase							:	Dict="relu"			,       __lowerCamelCase							:	Dict=2_5_6			,       __lowerCamelCase							:	List[Any]=0.1			,       __lowerCamelCase							:	Dict=0.0			,       __lowerCamelCase							:	Optional[int]=0.0			,       __lowerCamelCase							:	List[str]=0.02			,       __lowerCamelCase							:	Tuple=2			,       __lowerCamelCase							:	Optional[Any]=True			,       __lowerCamelCase							:	List[str]=1			,       __lowerCamelCase							:	int=0			,       __lowerCamelCase							:	int=2			,       __lowerCamelCase							:	int=1_0_2_4			,       **__lowerCamelCase							:	Union[str, Any]			,       ):
    UpperCAmelCase__	:List[str]      =      vocab_size
    UpperCAmelCase__	:str      =      d_model
    UpperCAmelCase__	:Dict      =      decoder_ffn_dim
    UpperCAmelCase__	:Any      =      decoder_layers
    UpperCAmelCase__	:List[Any]      =      decoder_attention_heads
    UpperCAmelCase__	:str      =      dropout
    UpperCAmelCase__	:List[Any]      =      attention_dropout
    UpperCAmelCase__	:List[Any]      =      activation_dropout
    UpperCAmelCase__	:Dict      =      activation_function
    UpperCAmelCase__	:Any      =      init_std
    UpperCAmelCase__	:Tuple      =      decoder_layerdrop
    UpperCAmelCase__	:Any      =      use_cache
    UpperCAmelCase__	:List[str]      =      decoder_layers
    UpperCAmelCase__	:List[Any]      =      scale_embedding  # scale factor will be sqrt(d_model) if True
    UpperCAmelCase__	:List[str]      =      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'''





from ..utils import DummyObject, requires_backends




class 				UpperCAmelCase			(			metaclass=_snake_case						):
 UpperCAmelCase				=					["note_seq"]


 def __init__(      self							:	List[str]			,       *__lowerCamelCase							:	int			,       **__lowerCamelCase							:	Optional[int] ):
    requires_backends(self			,       ['''note_seq'''] )


 @classmethod
 def        __SCREAMING_SNAKE_CASE					(      cls							:	Optional[Any]			,       *__lowerCamelCase							:	Dict			,       **__lowerCamelCase							:	Optional[Any] ):
    requires_backends(cls			,       ['''note_seq'''] )





 @classmethod
 def        __SCREAMING_SNAKE_CASE					(      cls							:	str			,       *__lowerCamelCase							:	Any			,       **__lowerCamelCase							:	Optional[Any] ):
    requires_backends(cls			,       ['''note_seq'''] )



