code: 
  
  
  
  import copy
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  __A       					=		logging.get_logger(__name__)
  
  __A       					=		{}
  
  
  
  
  
  
  class 	lowercase		(				snake_case__):
  
  
  
  
  
  
  	"""simple docstring"""
  
  
  	a__   :      List[str]	     =							"fsmt_decoder"
  
  
  
  
  	def __init__(			self			:		Any		,						__UpperCAmelCase			:		Union[str, Any]=0		,						__UpperCAmelCase			:		int=0  )    ->				str:
  							super().__init__()
  							UpperCAmelCase_=     vocab_size
  							UpperCAmelCase_=     bos_token_id
  
  
  
  
  
  
  class 	lowercase		(				snake_case__):
  
  
  
  
  
  
  	"""simple docstring"""
  
  
  	a__   :      List[Any]	     =							"fsmt"
  	a__   :      Union[str, Any]	     =							{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}
  
  
  
  
  	def __init__(			self			:		Union[str, Any]		,						__UpperCAmelCase			:		List[Any]=["en", "de"]		,						__UpperCAmelCase			:		Any=42_024		,						__UpperCAmelCase			:		Any=42_024		,						__UpperCAmelCase			:		Union[str, Any]="relu"		,						__UpperCAmelCase			:		Any=1_024		,						__UpperCAmelCase			:		Any=200		,						__UpperCAmelCase			:		Dict=1_024		,						__UpperCAmelCase			:		int=4_096		,						__UpperCAmelCase			:		str=12		,						__UpperCAmelCase			:		Union[str, Any]=16		,						__UpperCAmelCase			:		Optional[int]=0.0		,						__UpperCAmelCase			:		Dict=4_096		,						__UpperCAmelCase			:		Dict=12		,						__UpperCAmelCase			:		Optional[Any]=16		,						__UpperCAmelCase			:		List[Any]=0.0		,						__UpperCAmelCase			:		str=0.0		,						__UpperCAmelCase			:		Optional[int]=0.1		,						__UpperCAmelCase			:		int=0.0		,						__UpperCAmelCase			:		List[str]=0.02		,						__UpperCAmelCase			:		str=2		,						__UpperCAmelCase			:		Dict=True		,						__UpperCAmelCase			:		str=True		,						__UpperCAmelCase			:		int=False		,						__UpperCAmelCase			:		Union[str, Any]=5		,						__UpperCAmelCase			:		Optional[Any]=1.0		,						__UpperCAmelCase			:		Dict=False		,						__UpperCAmelCase			:		Tuple=True		,						__UpperCAmelCase			:		int=1		,						__UpperCAmelCase			:		Any=0		,						__UpperCAmelCase			:		Tuple=2		,						__UpperCAmelCase			:		int=2		,						**__UpperCAmelCase			:		Union[str, Any]		,						)    ->				Union[str, Any]:
  							UpperCAmelCase_=     langs
  							UpperCAmelCase_=     src_vocab_size
  							UpperCAmelCase_=     tgt_vocab_size
  							UpperCAmelCase_=     d_model  # encoder_embed_dim and decoder_embed_dim
  
  							UpperCAmelCase_=     encoder_ffn_dim
  							UpperCAmelCase_=     UpperCAmelCase_=     encoder_layers
  							UpperCAmelCase_=     encoder_attention_heads
  							UpperCAmelCase_=     encoder_layerdrop
  							UpperCAmelCase_=     decoder_layerdrop
  							UpperCAmelCase_=     decoder_ffn_dim
  							UpperCAmelCase_=     decoder_layers
  							UpperCAmelCase_=     decoder_attention_heads
  							UpperCAmelCase_=     max_position_embeddings
  							UpperCAmelCase_=     init_std  # Normal(0, this parameter)
  							UpperCAmelCase_=     activation_function
  
  							UpperCAmelCase_=     DecoderConfig(vocab_size=__UpperCAmelCase		,						bos_token_id=__UpperCAmelCase  )
  							if "decoder" in common_kwargs:
  													del common_kwargs["decoder"]
  
  							UpperCAmelCase_=     scale_embedding  # scale factor will be sqrt(d_model) if True
  
  							# 3 Types of Dropout
  							UpperCAmelCase_=     attention_dropout
  							UpperCAmelCase_=     activation_dropout
  							UpperCAmelCase_=     dropout
  
  							UpperCAmelCase_=     use_cache
  							super().__init__(
  							    pad_token_id=__UpperCAmelCase		,						bos_token_id=__UpperCAmelCase		,						eos_token_id=__UpperCAmelCase		,						decoder_start_token_id=__UpperCAmelCase		,						is_encoder_decoder=__UpperCAmelCase		,						tie_word_embeddings=__UpperCAmelCase		,						forced_eos_token_id=__UpperCAmelCase		,						max_length=__UpperCAmelCase		,						num_beams=__UpperCAmelCase		,						length_penalty=__UpperCAmelCase		,						early_stopping=__UpperCAmelCase		,						**__UpperCAmelCase		,						)
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		Dict  )    ->				Any:
  							UpperCAmelCase_=     copy.deepcopy(self.__dict__  )
  							UpperCAmelCase_=     self.decoder.to_dict()
  							UpperCAmelCase_=     self.__class__.model_type
  							return output
  
  
  
  
  
style_context: 
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  __A       					=		logging.get_logger(__name__)
  
  __A       					=		{
      '''ZinengTang/tvlt-base''': '''https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json''',
  }
  
  
  
  
  
  
  class 	lowercase		(				snake_case__):
  
  
  
  
  
  
  	"""simple docstring"""
  
  
  	a__   :      Tuple	     =							"tvlt"
  
  
  
  
  	def __init__(			self			:		List[str]		,						__UpperCAmelCase			:		List[str]=224		,						__UpperCAmelCase			:		List[str]=2_048		,						__UpperCAmelCase			:		Tuple=128		,						__UpperCAmelCase			:		Union[str, Any]=[16, 16]		,						__UpperCAmelCase			:		str=[16, 16]		,						__UpperCAmelCase			:		str=3		,						__UpperCAmelCase			:		List[str]=1		,						__UpperCAmelCase			:		Tuple=8		,						__UpperCAmelCase			:		Optional[Any]=768		,						__UpperCAmelCase			:		List[Any]=12		,						__UpperCAmelCase			:		Tuple=12		,						__UpperCAmelCase			:		List[str]=3_072		,						__UpperCAmelCase			:		List[Any]="gelu"		,						__UpperCAmelCase			:		str=0.0		,						__UpperCAmelCase			:		str=0.0		,						__UpperCAmelCase			:		List[Any]=0.02		,						__UpperCAmelCase			:		Optional[int]=1E-6		,						__UpperCAmelCase			:		Tuple=True		,						__UpperCAmelCase			:		List[Any]=False		,						__UpperCAmelCase			:		Union[str, Any]=16		,						__UpperCAmelCase			:		Any=512		,						__UpperCAmelCase			:		Optional[Any]=8		,						__UpperCAmelCase			:		Dict=2_048		,						__UpperCAmelCase			:		Dict=0.75		,						__UpperCAmelCase			:		Union[str, Any]=0.15		,						__UpperCAmelCase			:		Any="frame-level"		,						__UpperCAmelCase			:		int=True		,						__UpperCAmelCase			:		List[Any]=True		,						__UpperCAmelCase			:		Union[str, Any]="classification"		,						**__UpperCAmelCase			:		Any		,						)    ->				Tuple:
  							super().__init__(**__UpperCAmelCase  )
  
  							if audio_mask_type not in ("frame-level", "patch_level"):
  													raise ValueError(
  													    """audio_mask_type must be one of two acceptable strategies - {'frame_level', 'patch-level') """
  													    F"""got {audio_mask_type}"""  )
  
  							UpperCAmelCase_=     image_size
  							UpperCAmelCase_=     spectrogram_length
  							UpperCAmelCase_=     frequency_length
  							UpperCAmelCase_=     image_patch_size
  							UpperCAmelCase_=     audio_patch_size
  							UpperCAmelCase_=     num_image_channels
  							UpperCAmelCase_=     num_audio_channels
  							UpperCAmelCase_=     num_frames
  
  							UpperCAmelCase_=     hidden_size
  							UpperCAmelCase_=     num_hidden_layers
  							UpperCAmelCase_=     num_attention_heads
  							UpperCAmelCase_=     intermediate_size
  							UpperCAmelCase_=     hidden_act
  							UpperCAmelCase_=     hidden_dropout_prob
  							UpperCAmelCase_=     attention_probs_dropout_prob
  							UpperCAmelCase_=     initializer_range
  							UpperCAmelCase_=     layer_norm_eps
  							UpperCAmelCase_=     qkv_bias
  							UpperCAmelCase_=     use_mean_pooling
  
  							UpperCAmelCase_=     decoder_num_attention_heads
  							UpperCAmelCase_=     decoder_hidden_size
  							UpperCAmelCase_=     decoder_num_hidden_layers
  							UpperCAmelCase_=     decoder_intermediate_size
  							UpperCAmelCase_=     pixel_mask_ratio
  							UpperCAmelCase_=     audio_mask_ratio
  							UpperCAmelCase_=     audio_mask_type
  
  							UpperCAmelCase_=     task_matching
  							UpperCAmelCase_=     task_mae
  							UpperCAmelCase_=     loss_type
  
  
  
  
  