import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


_lowerCAmelCase        =       logging.get_logger(__name__)

_lowerCAmelCase        =       {
    """facebook/musicgen-small""": """https://huggingface.co/facebook/musicgen-small/resolve/main/config.json""",
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}






class     __UpperCAmelCase(    _a				):






 """simple docstring"""




 __magic_name__          =   """musicgen_decoder"""
 __magic_name__          =   ["""past_key_values"""]
 def __init__(    self ,       __magic_name__=2048 ,       __magic_name__=2048 ,       __magic_name__=24 ,       __magic_name__=4096 ,       __magic_name__=16 ,       __magic_name__=0.0 ,       __magic_name__=True ,       __magic_name__="gelu" ,       __magic_name__=1024 ,       __magic_name__=0.1 ,       __magic_name__=0.0 ,       __magic_name__=0.0 ,       __magic_name__=0.02 ,       __magic_name__=False ,       __magic_name__=4 ,       __magic_name__=2048 ,       __magic_name__=2048 ,       __magic_name__=None ,       __magic_name__=False ,       **__magic_name__ ,       ):

        """simple docstring"""

        A_							:       Optional[int]	      =				vocab_size
        A_							:       Tuple	      =				max_position_embeddings
        A_							:       Tuple	      =				hidden_size
        A_							:       List[Any]	      =				ffn_dim
        A_							:       Union[str, Any]	      =				num_hidden_layers
        A_							:       List[Any]	      =				num_attention_heads
        A_							:       List[str]	      =				dropout
        A_							:       List[Any]	      =				attention_dropout
        A_							:       int	      =				activation_dropout
        A_							:       Optional[int]	      =				activation_function
        A_							:       Any	      =				initializer_factor
        A_							:       str	      =				layerdrop
        A_							:       int	      =				use_cache
        A_							:       Optional[Any]	      =				scale_embedding  # scale factor will be sqrt(d_model) if True
        A_							:       List[Any]	      =				num_codebooks
        super().__init__(
            pad_token_id=__magic_name__ ,       bos_token_id=__magic_name__ ,       eos_token_id=__magic_name__ ,       tie_word_embeddings=__magic_name__ ,       **__magic_name__ ,       )






class     __UpperCAmelCase(    _a				):






 """simple docstring"""




 __magic_name__          =   """musicgen"""
 __magic_name__          =   True
 def __init__(    self ,       **__magic_name__      ):

        """simple docstring"""

        super().__init__(**__magic_name__      )
        if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
               raise ValueError('''Config has to be initialized with text_encoder, audio_encoder and decoder config'''      )

        A_							:       str	      =				kwargs.pop('''text_encoder'''      )
        A_							:       List[Any]	      =				text_encoder_config.pop('''model_type'''      )

        A_							:       Optional[int]	      =				kwargs.pop('''audio_encoder'''      )
        A_							:       List[Any]	      =				audio_encoder_config.pop('''model_type'''      )

        A_							:       Dict	      =				kwargs.pop('''decoder'''      )

        A_							:       Any	      =				AutoConfig.for_model(__magic_name__ ,       **__magic_name__      )
        A_							:       str	      =				AutoConfig.for_model(__magic_name__ ,       **__magic_name__      )
        A_							:       Union[str, Any]	      =				MusicgenDecoderConfig(**__magic_name__      )
        A_							:       Optional[Any]	      =				True
 @classmethod
 def  UpperCAmelCase   (    cls ,       __magic_name__ ,       __magic_name__ ,       __magic_name__ ,       **__magic_name__ ,       ):

        """simple docstring"""

        return cls(
            text_encoder=text_encoder_config.to_dict() ,       audio_encoder=audio_encoder_config.to_dict() ,       decoder=decoder_config.to_dict() ,       **__magic_name__ ,       )
 def  UpperCAmelCase   (    self      ):

        """simple docstring"""

        A_							:       int	      =				copy.deepcopy(self.__dict__      )
        A_							:       List[str]	      =				self.text_encoder.to_dict()
        A_							:       Tuple	      =				self.audio_encoder.to_dict()
        A_							:       Optional[Any]	      =				self.decoder.to_dict()
        A_							:       Optional[Any]	      =				self.__class__.model_type
        return output









import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


_UpperCamelCase       :				Tuple           =			logging.get_logger(__name__)







class 		_lowerCAmelCase(		_a):

  """simple docstring"""







  def __init__(   self    ,							*UpperCAmelCase    ,							**UpperCAmelCase      )->   None:
     warnings.warn(
         '''The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
         ''' Please use DetrImageProcessor instead.'''    ,							UpperCAmelCase    ,							)
     super().__init__(*UpperCAmelCase    ,							**UpperCAmelCase      )

