code: 
  
  
  
  
  """simple docstring"""
  
  from __future__ import annotations
  
  # Define the Gravitational Constant G and the function
  __A 		=			6.6_7_4_3e-1_1  # unit of G : m^3 * kg^-1 * s^-2
  
  
  
  def   UpperCamelCase__     (		lowercase__  :     float       ,     lowercase__  :     float       ,     lowercase__  :     float       ,     lowercase__  :     float   ):
  		snake_case		:						Any								=				mass_a * mass_a
  
  		if (force, mass_a, mass_a, distance).count(0   ) != 1:
  				raise ValueError("One and only one argument must be 0"   )
  		if force < 0:
  				raise ValueError("Gravitational force can not be negative"   )
  		if distance < 0:
  				raise ValueError("Distance can not be negative"   )
  		if mass_a < 0 or mass_a < 0:
  				raise ValueError("Mass can not be negative"   )
  		if force == 0:
  				snake_case		:						Tuple								=				GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
  				return {"force": force}
  		elif mass_a == 0:
  				snake_case		:						str								=				(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
  				return {"mass_1": mass_a}
  		elif mass_a == 0:
  				snake_case		:						Any								=				(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
  				return {"mass_2": mass_a}
  		elif distance == 0:
  				snake_case		:						List[str]								=				(GRAVITATIONAL_CONSTANT * product_of_mass / (force)) ** 0.5
  				return {"distance": distance}
  		raise ValueError("One and only one argument must be 0"   )
  
  
  # Run doctest
  if __name__ == "__main__":
  							import doctest
  
  							doctest.testmod()
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
  class 			lowerCamelCase__    (  lowerCamelCase_			):
  			a__ :      Tuple								=     ["""image_processor""", """tokenizer"""]
  			a__ :      List[Any]								=     """EfficientNetImageProcessor"""
  			a__ :      str								=     ("""BertTokenizer""", """BertTokenizerFast""")
  
  
  			def __init__(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					super().__init__(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							)
  
  
  			def __call__(     self				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE="max_length"				, SCREAMING_SNAKE_CASE=64				, SCREAMING_SNAKE_CASE=None				, **SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					if text is None and images is None:
  							raise ValueError("You have to specify either text or images. Both cannot be none."							)
  
  					if text is not None:
  							snake_case		:						Dict								=				self.tokenizer(
  							    SCREAMING_SNAKE_CASE				, padding=SCREAMING_SNAKE_CASE				, max_length=SCREAMING_SNAKE_CASE				, return_tensors=SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  					if images is not None:
  							snake_case		:						Tuple								=				self.image_processor(SCREAMING_SNAKE_CASE				, return_tensors=SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  					if text is not None and images is not None:
  							snake_case		:						Dict								=				image_features.pixel_values
  							return encoding
  					elif text is not None:
  							return encoding
  					else:
  							return BatchEncoding(data=dict(**SCREAMING_SNAKE_CASE							)				, tensor_type=SCREAMING_SNAKE_CASE							)
  
  
  			def 							lowerCamelCase_				(     self				, *SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  
  			def 							lowerCamelCase_				(     self				, *SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					return self.tokenizer.decode(*SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)
  
  
  
  			@property
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Optional[Any]								=				self.tokenizer.model_input_names
  					snake_case		:						Any								=				self.image_processor.model_input_names
  					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)
  
  