code: import copy
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _SCREAMING_SNAKE_CASE   						=    logging.get_logger(__name__)
  
  _SCREAMING_SNAKE_CASE   						=    {
      """facebook/sam-vit-huge""": """https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json""",
      """facebook/sam-vit-large""": """https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json""",
      """facebook/sam-vit-base""": """https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json""",
  }
  
  
  
  
  
  
  
  class 					UpperCAmelCase_				(							_a    ):
  
  
  
  
      def __init__(					self  :   List[str]      ,      lowerCAmelCase  :   str=256      ,      lowerCAmelCase  :   Any=1024      ,      lowerCAmelCase  :   List[str]=16      ,      lowerCAmelCase  :   Union[str, Any]=16      ,      lowerCAmelCase  :   int=4      ,      lowerCAmelCase  :   List[Any]="gelu"      ,      lowerCAmelCase  :   str=1e-6      ,      **lowerCAmelCase  :   Union[str, Any]      ,      )	-> Union[str, Any]:
        super().__init__(**lowerCAmelCase   )
        a__     		=     hidden_size
        a__     		=     image_size
        a__     		=     patch_size
        a__     		=     image_size // patch_size
        a__     		=     mask_input_channels
        a__     		=     num_point_embeddings
        a__     		=     hidden_act
        a__     		=     layer_norm_eps
  
  
  
  
  
  
  
  class 					UpperCAmelCase_				(							_a    ):
  
  
  
  
      def __init__(					self  :   Dict      ,      lowerCAmelCase  :   str=256      ,      lowerCAmelCase  :   Union[str, Any]="relu"      ,      lowerCAmelCase  :   Optional[int]=2048      ,      lowerCAmelCase  :   Any=2      ,      lowerCAmelCase  :   Any=8      ,      lowerCAmelCase  :   Optional[Any]=2      ,      lowerCAmelCase  :   Optional[Any]=3      ,      lowerCAmelCase  :   Union[str, Any]=3      ,      lowerCAmelCase  :   List[str]=256      ,      lowerCAmelCase  :   Optional[Any]=1e-6      ,      **lowerCAmelCase  :   Any      ,      )	-> int:
        super().__init__(**lowerCAmelCase   )
        a__     		=     hidden_size
        a__     		=     hidden_act
        a__     		=     mlp_dim
        a__     		=     num_hidden_layers
        a__     		=     num_attention_heads
        a__     		=     attention_downsample_rate
        a__     		=     num_multimask_outputs
        a__     		=     iou_head_depth
        a__     		=     iou_head_hidden_dim
        a__     		=     layer_norm_eps
  
  
  
  
  
  
  
  class 					UpperCAmelCase_				(							_a    ):
  
  
  
  
      def __init__(					self  :   Optional[Any]      ,      lowerCAmelCase  :   Optional[Any]=768      ,      lowerCAmelCase  :   int=256      ,      lowerCAmelCase  :   Tuple=12      ,      lowerCAmelCase  :   List[str]=12      ,      lowerCAmelCase  :   Tuple=3      ,      lowerCAmelCase  :   Any=1024      ,      lowerCAmelCase  :   Dict=16      ,      lowerCAmelCase  :   Dict="gelu"      ,      lowerCAmelCase  :   List[Any]=1e-0_6      ,      lowerCAmelCase  :   Any=0.0      ,      lowerCAmelCase  :   Optional[Any]=1e-1_0      ,      lowerCAmelCase  :   Tuple=True      ,      lowerCAmelCase  :   Tuple=4.0      ,      lowerCAmelCase  :   Optional[Any]=True      ,      lowerCAmelCase  :   List[str]=True      ,      lowerCAmelCase  :   Dict=14      ,      lowerCAmelCase  :   Optional[int]=[2, 5, 8, 11]      ,      lowerCAmelCase  :   List[str]=128      ,      lowerCAmelCase  :   List[str]=None      ,      **lowerCAmelCase  :   str      ,      )	-> Optional[int]:
        super().__init__(**lowerCAmelCase   )
  
        a__     		=     hidden_size
        a__     		=     output_channels
        a__     		=     num_hidden_layers
        a__     		=     num_attention_heads
        a__     		=     num_channels
        a__     		=     image_size
        a__     		=     patch_size
        a__     		=     hidden_act
        a__     		=     layer_norm_eps
        a__     		=     attention_dropout
        a__     		=     initializer_range
        a__     		=     qkv_bias
        a__     		=     mlp_ratio
        a__     		=     use_abs_pos
        a__     		=     use_rel_pos
        a__     		=     window_size
        a__     		=     global_attn_indexes
        a__     		=     num_pos_feats
        a__     		=     int(hidden_size * mlp_ratio   ) if mlp_dim is None else mlp_dim
  
  
  
  
  
  
  
  class 					UpperCAmelCase_				(							_a    ):
      UpperCAmelCase_			:       Optional[Any]						 =							'sam'
      UpperCAmelCase_			:       List[Any]						 =							True
  
  
  
  
      def __init__(					self  :   Dict      ,      lowerCAmelCase  :   Any=None      ,      lowerCAmelCase  :   Optional[Any]=None      ,      lowerCAmelCase  :   Optional[Any]=None      ,      lowerCAmelCase  :   str=0.02      ,      **lowerCAmelCase  :   int      ,      )	-> Dict:
        super().__init__(**lowerCAmelCase   )
        a__     		=     vision_config if vision_config is not None else {}
        a__     		=     prompt_encoder_config if prompt_encoder_config is not None else {}
        a__     		=     mask_decoder_config if mask_decoder_config is not None else {}
  
        if isinstance(lowerCAmelCase      ,      lowerCAmelCase   ):
          a__     		=     vision_config.to_dict()
        if isinstance(lowerCAmelCase      ,      lowerCAmelCase   ):
          a__     		=     prompt_encoder_config.to_dict()
        if isinstance(lowerCAmelCase      ,      lowerCAmelCase   ):
          a__     		=     mask_decoder_config.to_dict()
  
        a__     		=     SamVisionConfig(**lowerCAmelCase   )
        a__     		=     SamPromptEncoderConfig(**lowerCAmelCase   )
        a__     		=     SamMaskDecoderConfig(**lowerCAmelCase   )
        a__     		=     initializer_range
  
  
  
  
      def 						__lowerCamelCase (					self  :   Optional[Any]   )	-> Union[str, Any]:
        a__     		=     copy.deepcopy(self.__dict__   )
        a__     		=     self.vision_config.to_dict()
        a__     		=     self.prompt_encoder_config.to_dict()
        a__     		=     self.mask_decoder_config.to_dict()
        a__     		=     self.__class__.model_type
        return output
  
  
style_context: def 				__lowercase	(						lowerCamelCase__ ,				lowerCamelCase__					)				->Optional[int]:
  
    '''simple docstring'''
  
  
  
  
    sequence.append(lowerCamelCase__					)
  
    a__     		=     0
    while sequence[index] != target:
      index += 1
  
    sequence.pop()
  
    if index == len(lowerCamelCase__					):
      return None
  
    return index
  
  
  if __name__ == "__main__":
       _SCREAMING_SNAKE_CASE   						=    input("""Enter numbers separated by comma:\n""").strip()
       _SCREAMING_SNAKE_CASE   						=    [int(item) for item in user_input.split(""",""")]
  
       _SCREAMING_SNAKE_CASE   						=    input("""Enter a single number to be found in the list:\n""")
       _SCREAMING_SNAKE_CASE   						=    int(target_input)
       _SCREAMING_SNAKE_CASE   						=    sentinel_linear_search(sequence, target)
       if result is not None:
            print(F"""{target} found at positions: {result}""")
       else:
            print("""Not found""")
  
  