code: 
  
  
  
  from typing import List, Optional, Tuple
  
  from tokenizers import pre_tokenizers
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_clip import CLIPTokenizer
  
  
  __A       					=		logging.get_logger(__name__)
  
  __A       					=		{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}
  
  __A       					=		{
      '''vocab_file''': {
          '''openai/clip-vit-base-patch32''': '''https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json''',
      },
      '''merges_file''': {
          '''openai/clip-vit-base-patch32''': '''https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt''',
      },
      '''tokenizer_file''': {
          '''openai/clip-vit-base-patch32''': (
              '''https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json'''
          ),
      },
  }
  
  __A       					=		{
      '''openai/clip-vit-base-patch32''': 77,
  }
  
  
  
  
  
  
  class 	lowercase		(				snake_case__):
  
  
  
  
  
  
  	"""simple docstring"""
  
  
  	a__   :      Any	     =							VOCAB_FILES_NAMES
  	a__   :      Tuple	     =							PRETRAINED_VOCAB_FILES_MAP
  	a__   :      List[Any]	     =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  	a__   :      List[Any]	     =							["input_ids", "attention_mask"]
  	a__   :      Union[str, Any]	     =							CLIPTokenizer
  
  
  
  
  	def __init__(			self			:		Dict		,						__UpperCAmelCase			:		Optional[Any]=None		,						__UpperCAmelCase			:		int=None		,						__UpperCAmelCase			:		Dict=None		,						__UpperCAmelCase			:		Optional[Any]="<|endoftext|>"		,						__UpperCAmelCase			:		int="<|startoftext|>"		,						__UpperCAmelCase			:		Optional[int]="<|endoftext|>"		,						__UpperCAmelCase			:		Optional[Any]="<|endoftext|>"		,						**__UpperCAmelCase			:		List[str]		,						)    ->				str:
  							super().__init__(
  							    __UpperCAmelCase		,						__UpperCAmelCase		,						tokenizer_file=__UpperCAmelCase		,						unk_token=__UpperCAmelCase		,						bos_token=__UpperCAmelCase		,						eos_token=__UpperCAmelCase		,						pad_token=__UpperCAmelCase		,						**__UpperCAmelCase		,						)
  
  							if not isinstance(self.backend_tokenizer.pre_tokenizer		,						pre_tokenizers.Sequence  ):
  													raise ValueError(
  													    """The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"""
  													    """ heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"""
  													    """ to be compatible with this version.The easiest way to do so is"""
  													    """ `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"""
  													    """ to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"""
  													    """ transformers."""  )
  
  							self._wrap_decode_method_backend_tokenizer()
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		Any  )    ->				List[Any]:
  							UpperCAmelCase_=     self.backend_tokenizer.decode
  
  							def new_decode_method(*__UpperCAmelCase			:		Any		,						**__UpperCAmelCase			:		Union[str, Any]  ):
  													UpperCAmelCase_=     orig_decode_method(*__UpperCAmelCase		,						**__UpperCAmelCase  )
  													UpperCAmelCase_=     text.replace(self.backend_tokenizer.model.end_of_word_suffix		,						""" """  ).strip()
  													return text
  
  							UpperCAmelCase_=     new_decode_method
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		Optional[int]		,						__UpperCAmelCase			:		List[int]		,						__UpperCAmelCase			:		Optional[List[int]] = None  )    ->				List[int]:
  							UpperCAmelCase_=     [self.bos_token_id]
  							UpperCAmelCase_=     [self.eos_token_id]
  
  							if token_ids_a is None:
  													return bos_token + token_ids_a + eos_token
  							return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		int		,						__UpperCAmelCase			:		List[int]		,						__UpperCAmelCase			:		Optional[List[int]] = None  )    ->				List[int]:
  							UpperCAmelCase_=     [self.bos_token_id]
  							UpperCAmelCase_=     [self.eos_token_id]
  
  							if token_ids_a is None:
  													return len(bos_token + token_ids_a + eos_token  ) * [0]
  							return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token  ) * [0]
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		str		,						__UpperCAmelCase			:		str		,						__UpperCAmelCase			:		Optional[str] = None  )    ->				Tuple[str]:
  							UpperCAmelCase_=     self._tokenizer.model.save(__UpperCAmelCase		,						name=__UpperCAmelCase  )
  							return tuple(__UpperCAmelCase  )
  
  
  
  
  
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
  
  
  
  
  