code: 
  
  import copy
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowerCamelCase__           =				logging.get_logger(__name__)
  
  lowerCamelCase__           =				{
      '''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	(     UpperCamelCase_      ):
  
  
  
  
  					def __init__( self :					Any      ,_lowerCAmelCase :					int=256      ,_lowerCAmelCase :					List[Any]=1_024      ,_lowerCAmelCase :					Tuple=16      ,_lowerCAmelCase :					int=16      ,_lowerCAmelCase :					Optional[Any]=4      ,_lowerCAmelCase :					List[str]="gelu"      ,_lowerCAmelCase :					Optional[Any]=1E-6      ,**_lowerCAmelCase :					Optional[int]      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(**__SCREAMING_SNAKE_CASE						)
  							__snake_case		       =     hidden_size
  							__snake_case		       =     image_size
  							__snake_case		       =     patch_size
  							__snake_case		       =     image_size // patch_size
  							__snake_case		       =     mask_input_channels
  							__snake_case		       =     num_point_embeddings
  							__snake_case		       =     hidden_act
  							__snake_case		       =     layer_norm_eps
  
  
  
  
  class 					UpperCamelCase	(     UpperCamelCase_      ):
  
  
  
  
  					def __init__( self :					Any      ,_lowerCAmelCase :					List[Any]=256      ,_lowerCAmelCase :					Tuple="relu"      ,_lowerCAmelCase :					str=2_048      ,_lowerCAmelCase :					Optional[Any]=2      ,_lowerCAmelCase :					Tuple=8      ,_lowerCAmelCase :					Dict=2      ,_lowerCAmelCase :					int=3      ,_lowerCAmelCase :					Dict=3      ,_lowerCAmelCase :					Any=256      ,_lowerCAmelCase :					Any=1E-6      ,**_lowerCAmelCase :					Dict      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(**__SCREAMING_SNAKE_CASE						)
  							__snake_case		       =     hidden_size
  							__snake_case		       =     hidden_act
  							__snake_case		       =     mlp_dim
  							__snake_case		       =     num_hidden_layers
  							__snake_case		       =     num_attention_heads
  							__snake_case		       =     attention_downsample_rate
  							__snake_case		       =     num_multimask_outputs
  							__snake_case		       =     iou_head_depth
  							__snake_case		       =     iou_head_hidden_dim
  							__snake_case		       =     layer_norm_eps
  
  
  
  
  class 					UpperCamelCase	(     UpperCamelCase_      ):
  
  
  
  
  					def __init__( self :					List[str]      ,_lowerCAmelCase :					List[str]=768      ,_lowerCAmelCase :					Dict=256      ,_lowerCAmelCase :					List[Any]=12      ,_lowerCAmelCase :					List[str]=12      ,_lowerCAmelCase :					Optional[Any]=3      ,_lowerCAmelCase :					str=1_024      ,_lowerCAmelCase :					Union[str, Any]=16      ,_lowerCAmelCase :					List[Any]="gelu"      ,_lowerCAmelCase :					int=1E-06      ,_lowerCAmelCase :					Optional[Any]=0.0      ,_lowerCAmelCase :					Tuple=1E-10      ,_lowerCAmelCase :					Optional[int]=True      ,_lowerCAmelCase :					Tuple=4.0      ,_lowerCAmelCase :					int=True      ,_lowerCAmelCase :					str=True      ,_lowerCAmelCase :					List[str]=14      ,_lowerCAmelCase :					str=[2, 5, 8, 11]      ,_lowerCAmelCase :					Dict=128      ,_lowerCAmelCase :					Any=None      ,**_lowerCAmelCase :					Tuple      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(**__SCREAMING_SNAKE_CASE						)
  
  							__snake_case		       =     hidden_size
  							__snake_case		       =     output_channels
  							__snake_case		       =     num_hidden_layers
  							__snake_case		       =     num_attention_heads
  							__snake_case		       =     num_channels
  							__snake_case		       =     image_size
  							__snake_case		       =     patch_size
  							__snake_case		       =     hidden_act
  							__snake_case		       =     layer_norm_eps
  							__snake_case		       =     attention_dropout
  							__snake_case		       =     initializer_range
  							__snake_case		       =     qkv_bias
  							__snake_case		       =     mlp_ratio
  							__snake_case		       =     use_abs_pos
  							__snake_case		       =     use_rel_pos
  							__snake_case		       =     window_size
  							__snake_case		       =     global_attn_indexes
  							__snake_case		       =     num_pos_feats
  							__snake_case		       =     int(hidden_size * mlp_ratio						) if mlp_dim is None else mlp_dim
  
  
  
  
  class 					UpperCamelCase	(     UpperCamelCase_      ):
  					__UpperCamelCase						=   """sam"""
  					__UpperCamelCase						=   True
  
  
  
  
  					def __init__( self :					List[str]      ,_lowerCAmelCase :					Union[str, Any]=None      ,_lowerCAmelCase :					Any=None      ,_lowerCAmelCase :					List[Any]=None      ,_lowerCAmelCase :					List[Any]=0.0_2      ,**_lowerCAmelCase :					Tuple      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(**__SCREAMING_SNAKE_CASE						)
  							__snake_case		       =     vision_config if vision_config is not None else {}
  							__snake_case		       =     prompt_encoder_config if prompt_encoder_config is not None else {}
  							__snake_case		       =     mask_decoder_config if mask_decoder_config is not None else {}
  
  							if isinstance(__SCREAMING_SNAKE_CASE      ,__SCREAMING_SNAKE_CASE						):
  									__snake_case		       =     vision_config.to_dict()
  							if isinstance(__SCREAMING_SNAKE_CASE      ,__SCREAMING_SNAKE_CASE						):
  									__snake_case		       =     prompt_encoder_config.to_dict()
  							if isinstance(__SCREAMING_SNAKE_CASE      ,__SCREAMING_SNAKE_CASE						):
  									__snake_case		       =     mask_decoder_config.to_dict()
  
  							__snake_case		       =     SamVisionConfig(**__SCREAMING_SNAKE_CASE						)
  							__snake_case		       =     SamPromptEncoderConfig(**__SCREAMING_SNAKE_CASE						)
  							__snake_case		       =     SamMaskDecoderConfig(**__SCREAMING_SNAKE_CASE						)
  							__snake_case		       =     initializer_range
  
  
  
  
  
  
  
  					def 							UpperCamelCase_						( self :					Any						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     copy.deepcopy(self.__dict__						)
  							__snake_case		       =     self.vision_config.to_dict()
  							__snake_case		       =     self.prompt_encoder_config.to_dict()
  							__snake_case		       =     self.mask_decoder_config.to_dict()
  							__snake_case		       =     self.__class__.model_type
  							return output
  
  
  
  
  
  
style_context: import os
  from string import ascii_letters
  
  lowerCamelCase__           =				ascii_letters + ' \t\n'
  
  
  
  def 							_lowerCamelCase(				)  ->   dict[str, None]:
  		__snake_case		       =     os.path.split(os.path.realpath(__snake_case	)	)
  		__snake_case		       =     {}
  		with open(path[0] + "/dictionary.txt"	) as dictionary_file:
  				for word in dictionary_file.read().split("\n"	):
  						__snake_case		       =     None
  		return english_words
  
  
  lowerCamelCase__           =				load_dictionary()
  
  
  
  def 							_lowerCamelCase(				__snake_case	)  ->   float:
  		__snake_case		       =     message.upper()
  		__snake_case		       =     remove_non_letters(__snake_case	)
  		__snake_case		       =     message.split()
  		__snake_case		       =     len([word for word in possible_words if word in ENGLISH_WORDS]	)
  		return float(__snake_case	) / len(__snake_case	)
  
  
  
  def 							_lowerCamelCase(				__snake_case	)  ->   str:
  		return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE	)
  
  
  
  def 							_lowerCamelCase(				__snake_case						,						__snake_case = 20						,						__snake_case = 85	)  ->   bool:
  		__snake_case		       =     get_english_count(__snake_case	) * 100 >= word_percentage
  		__snake_case		       =     len(remove_non_letters(__snake_case	)	)
  		__snake_case		       =     (float(__snake_case	) / len(__snake_case	)) * 100
  		__snake_case		       =     message_letters_percentage >= letter_percentage
  		return words_match and letters_match
  
  
  if __name__ == "__main__":
  		import doctest
  
  		doctest.testmod()
  
  
  
  
  
  