code: 
  
  
  
  
  
  import copy
  from typing import Dict
  
  from ...generation.configuration_utils import GenerationConfig
  from ...utils import logging
  
  
  _lowercase		:     Optional[Any] 					=logging.get_logger(__name__)
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	Dict							=				'semantic'
  
  
  
  					def __init__(		self    :    int					,			lowerCamelCase    :    Optional[Any]=1_00_00					,			lowerCamelCase    :    Optional[Any]=True					,			lowerCamelCase    :    Optional[Any]=7_68					,			lowerCamelCase    :    List[Any]=False					,			lowerCamelCase    :    Union[str, Any]=False					,			lowerCamelCase    :    List[Any]=False					,			lowerCamelCase    :    Union[str, Any]=False					,			lowerCamelCase    :    int=0.7					,			lowerCamelCase    :    Any=True					,			lowerCamelCase    :    Dict=1_00_48					,			lowerCamelCase    :    List[str]=12_95_95					,			lowerCamelCase    :    str=12_95_99					,			lowerCamelCase    :    str=1_00_00					,			lowerCamelCase    :    Union[str, Any]=2_56					,			lowerCamelCase    :    Optional[int]=49.9					,			**lowerCamelCase    :    List[Any]					,			):
  							super().__init__(
  							    temperature=lowerCamelCase					,			do_sample=lowerCamelCase					,			eos_token_id=lowerCamelCase					,			renormalize_logits=lowerCamelCase					,			max_new_tokens=lowerCamelCase					,			output_scores=lowerCamelCase					,			return_dict_in_generate=lowerCamelCase					,			output_hidden_states=lowerCamelCase					,			output_attentions=lowerCamelCase					,			**lowerCamelCase					,			)
  
  							lowerCamelCase_  :    int   	=			text_encoding_offset
  							lowerCamelCase_  :    int   	=			text_pad_token
  							lowerCamelCase_  :    Any   	=			eos_token_id
  							lowerCamelCase_  :    List[str]   	=			semantic_infer_token
  							lowerCamelCase_  :    str   	=			semantic_vocab_size
  							lowerCamelCase_  :    Optional[int]   	=			max_input_semantic_length
  							lowerCamelCase_  :    Optional[int]   	=			semantic_rate_hz
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	int							=				'coarse_acoustics'
  
  
  
  					def __init__(		self    :    int					,			lowerCamelCase    :    Any=True					,			lowerCamelCase    :    Optional[int]=False					,			lowerCamelCase    :    List[Any]=False					,			lowerCamelCase    :    Tuple=False					,			lowerCamelCase    :    Optional[Any]=False					,			lowerCamelCase    :    Optional[int]=0.7					,			lowerCamelCase    :    List[str]=True					,			lowerCamelCase    :    Optional[Any]=1_20_48					,			lowerCamelCase    :    Optional[int]=75					,			lowerCamelCase    :    Union[str, Any]=2					,			lowerCamelCase    :    Tuple=1_20_50					,			lowerCamelCase    :    Dict=2_56					,			lowerCamelCase    :    int = 6_30					,			lowerCamelCase    :    int = 60					,			**lowerCamelCase    :    List[Any]					,			):
  							super().__init__(
  							    temperature=lowerCamelCase					,			do_sample=lowerCamelCase					,			renormalize_logits=lowerCamelCase					,			output_scores=lowerCamelCase					,			return_dict_in_generate=lowerCamelCase					,			output_hidden_states=lowerCamelCase					,			output_attentions=lowerCamelCase					,			**lowerCamelCase					,			)
  
  							lowerCamelCase_  :    Tuple   	=			coarse_semantic_pad_token
  							lowerCamelCase_  :    List[str]   	=			coarse_rate_hz
  							lowerCamelCase_  :    Optional[int]   	=			n_coarse_codebooks
  							lowerCamelCase_  :    str   	=			coarse_infer_token
  							lowerCamelCase_  :    Tuple   	=			max_coarse_input_length
  							lowerCamelCase_  :    Optional[int]   	=			max_coarse_history
  							lowerCamelCase_  :    Any   	=			sliding_window_len
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	Optional[int]							=				'fine_acoustics'
  
  
  
  					def __init__(		self    :    List[Any]					,			lowerCamelCase    :    Any=0.5					,			lowerCamelCase    :    Optional[int]=5_12					,			lowerCamelCase    :    Union[str, Any]=10_24					,			lowerCamelCase    :    List[Any]=8					,			**lowerCamelCase    :    List[str]					,			):
  							super().__init__(temperature=lowerCamelCase	)
  
  							lowerCamelCase_  :    List[Any]   	=			max_fine_history_length
  							lowerCamelCase_  :    Union[str, Any]   	=			max_fine_input_length
  							lowerCamelCase_  :    Tuple   	=			n_fine_codebooks
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	Dict							=				'bark'
  					_a			:	Union[str, Any]							=				True
  
  
  
  					def __init__(		self    :    Tuple					,			lowerCamelCase    :    Dict = None					,			lowerCamelCase    :    Dict = None					,			lowerCamelCase    :    Dict = None					,			lowerCamelCase    :    Dict=2_40_00					,			lowerCamelCase    :    Union[str, Any]=10_24					,			**lowerCamelCase    :    Optional[int]					,			):
  							if semantic_config is None:
  									lowerCamelCase_  :    Optional[Any]   	=			{}
  									logger.info('semantic_config is None. initializing the semantic model with default values.'	)
  
  							if coarse_acoustics_config is None:
  									lowerCamelCase_  :    Tuple   	=			{}
  									logger.info('coarse_acoustics_config is None. initializing the coarse model with default values.'	)
  
  							if fine_acoustics_config is None:
  									lowerCamelCase_  :    Optional[int]   	=			{}
  									logger.info('fine_acoustics_config is None. initializing the fine model with default values.'	)
  
  							lowerCamelCase_  :    Union[str, Any]   	=			BarkSemanticGenerationConfig(**lowerCamelCase	)
  							lowerCamelCase_  :    Optional[int]   	=			BarkCoarseGenerationConfig(**lowerCamelCase	)
  							lowerCamelCase_  :    Optional[Any]   	=			BarkFineGenerationConfig(**lowerCamelCase	)
  
  							lowerCamelCase_  :    Any   	=			sample_rate
  							lowerCamelCase_  :    Union[str, Any]   	=			codebook_size
  
  
  
  					@classmethod
  					def      __a    (		cls    :    Tuple					,			lowerCamelCase    :    BarkSemanticGenerationConfig					,			lowerCamelCase    :    BarkCoarseGenerationConfig					,			lowerCamelCase    :    BarkFineGenerationConfig					,			**lowerCamelCase    :    Tuple					,			):
  							return cls(
  							    semantic_config=semantic_config.to_dict()					,			coarse_acoustics_config=coarse_acoustics_config.to_dict()					,			fine_acoustics_config=fine_acoustics_config.to_dict()					,			**lowerCamelCase					,			)
  
  
  
  
  
  					def      __a    (		self    :    List[Any]	):
  							lowerCamelCase_  :    int   	=			copy.deepcopy(self.__dict__	)
  
  							lowerCamelCase_  :    Optional[int]   	=			self.semantic_config.to_dict()
  							lowerCamelCase_  :    Optional[Any]   	=			self.coarse_acoustics_config.to_dict()
  							lowerCamelCase_  :    List[Any]   	=			self.fine_acoustics_config.to_dict()
  
  							lowerCamelCase_  :    Optional[Any]   	=			self.__class__.model_type
  							return output
  
style_context: 
  
  
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _lowercase		:     Dict 					=logging.get_logger(__name__)
  
  _lowercase		:     Any 					={
      """dandelin/vilt-b32-mlm""": """https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"""
  }
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	List[str]							=				'vilt'
  
  
  
  					def __init__(		self    :    int					,			lowerCamelCase    :    Any=3_05_22					,			lowerCamelCase    :    Union[str, Any]=2					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    str=40					,			lowerCamelCase    :    List[str]=7_68					,			lowerCamelCase    :    Optional[int]=12					,			lowerCamelCase    :    List[Any]=12					,			lowerCamelCase    :    List[str]=30_72					,			lowerCamelCase    :    Union[str, Any]="gelu"					,			lowerCamelCase    :    int=0.0					,			lowerCamelCase    :    str=0.0					,			lowerCamelCase    :    int=0.02					,			lowerCamelCase    :    Union[str, Any]=1E-12					,			lowerCamelCase    :    Dict=3_84					,			lowerCamelCase    :    List[str]=32					,			lowerCamelCase    :    Dict=3					,			lowerCamelCase    :    List[str]=True					,			lowerCamelCase    :    int=-1					,			lowerCamelCase    :    List[Any]=False					,			lowerCamelCase    :    Any=-1					,			**lowerCamelCase    :    str					,			):
  							super().__init__(tie_word_embeddings=lowerCamelCase					,			**lowerCamelCase	)
  
  							lowerCamelCase_  :    str   	=			vocab_size
  							lowerCamelCase_  :    Dict   	=			type_vocab_size
  							lowerCamelCase_  :    str   	=			modality_type_vocab_size
  							lowerCamelCase_  :    Optional[Any]   	=			max_position_embeddings
  
  							lowerCamelCase_  :    List[Any]   	=			hidden_size
  							lowerCamelCase_  :    Union[str, Any]   	=			num_hidden_layers
  							lowerCamelCase_  :    Any   	=			num_attention_heads
  							lowerCamelCase_  :    List[Any]   	=			intermediate_size
  							lowerCamelCase_  :    Union[str, Any]   	=			hidden_act
  							lowerCamelCase_  :    Any   	=			hidden_dropout_prob
  							lowerCamelCase_  :    Optional[int]   	=			attention_probs_dropout_prob
  							lowerCamelCase_  :    Any   	=			initializer_range
  							lowerCamelCase_  :    str   	=			layer_norm_eps
  
  							lowerCamelCase_  :    Optional[Any]   	=			image_size
  							lowerCamelCase_  :    List[Any]   	=			patch_size
  							lowerCamelCase_  :    Tuple   	=			num_channels
  							lowerCamelCase_  :    Optional[Any]   	=			qkv_bias
  							lowerCamelCase_  :    Optional[int]   	=			max_image_length
  							lowerCamelCase_  :    Optional[Any]   	=			num_images
  