code: 
  
  
  
  from __future__ import annotations
  
  from typing import Generic, TypeVar
  
  __A       					=		TypeVar('''T''')
  
  
  
  
  
  
  class 	lowercase		(				Generic[T]):
  
  
  
  
  
  
  	"""simple docstring"""
  
  
  	def __init__(			self			:		Dict		,						__UpperCAmelCase			:		T  )    ->				List[str]:
  							UpperCAmelCase_=     data  # Assign data
  							UpperCAmelCase_=     None  # Initialize next as null
  							UpperCAmelCase_=     None  # Initialize prev as null
  
  
  
  
  
  
  class 	lowercase		(				Generic[T]):
  
  
  
  
  
  
  	"""simple docstring"""
  
  
  	def __init__(			self			:		int  )    ->				None:
  							UpperCAmelCase_=     None
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		int		,						__UpperCAmelCase			:		T  )    ->				None:
  							if self.head is None:
  													UpperCAmelCase_=     Node(__UpperCAmelCase  )
  							else:
  													UpperCAmelCase_=     Node(__UpperCAmelCase  )
  													UpperCAmelCase_=     new_node
  													UpperCAmelCase_=     self.head
  													UpperCAmelCase_=     None
  													UpperCAmelCase_=     new_node
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		List[str]  )    ->				T | None:
  							if self.head is None:
  													return None
  							else:
  													assert self.head is not None
  													UpperCAmelCase_=     self.head.data
  													UpperCAmelCase_=     self.head.next
  													if self.head is not None:
  																			UpperCAmelCase_=     None
  													return temp
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		Union[str, Any]  )    ->				T | None:
  							return self.head.data if self.head is not None else None
  
  
  
  
  	def __len__(			self			:		str  )    ->				int:
  							UpperCAmelCase_=     self.head
  							UpperCAmelCase_=     0
  							while temp is not None:
  													count += 1
  													UpperCAmelCase_=     temp.next
  							return count
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		List[str]  )    ->				bool:
  							return self.head is None
  
  
  
  
  	def 						_SCREAMING_SNAKE_CASE	(			self			:		List[str]  )    ->				None:
  							print("""stack elements are:"""  )
  							UpperCAmelCase_=     self.head
  							while temp is not None:
  													print(temp.data		,						end="""->"""  )
  													UpperCAmelCase_=     temp.next
  
  
  # Code execution starts here
  if __name__ == "__main__":
  	# Start with the empty stack
  	__A       					=		Stack()
  
  	# Insert 4 at the beginning. So stack becomes 4->None
  	print('''Stack operations using Doubly LinkedList''')
  	stack.push(4)
  
  	# Insert 5 at the beginning. So stack becomes 4->5->None
  	stack.push(5)
  
  	# Insert 6 at the beginning. So stack becomes 4->5->6->None
  	stack.push(6)
  
  	# Insert 7 at the beginning. So stack becomes 4->5->6->7->None
  	stack.push(7)
  
  	# Print the stack
  	stack.print_stack()
  
  	# Print the top element
  	print('''\nTop element is ''', stack.top())
  
  	# Print the stack size
  	print('''Size of the stack is ''', len(stack))
  
  	# pop the top element
  	stack.pop()
  
  	# pop the top element
  	stack.pop()
  
  	# two elements have now been popped off
  	stack.print_stack()
  
  	# Print True if the stack is empty else False
  	print('''\nstack is empty:''', stack.is_empty())
  
  
  
  
  
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
  
  
  
  
  