



'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCamelCase							       =		logging.get_logger(__name__)

_UpperCamelCase							       =		{
    'dandelin/vilt-b32-mlm': 'https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'
}






class       lowerCamelCase_					(       SCREAMING_SNAKE_CASE_  ):
  """simple docstring"""




  a_							      ="""vilt"""




  def __init__(				self   :			Optional[int]    ,			_a   :			Any=3_0522    ,			_a   :			Union[str, Any]=2    ,			_a   :			List[Any]=2    ,			_a   :			Optional[Any]=40    ,			_a   :			Optional[Any]=768    ,			_a   :			Optional[Any]=12    ,			_a   :			Union[str, Any]=12    ,			_a   :			Any=3072    ,			_a   :			List[Any]="gelu"    ,			_a   :			Dict=0.0    ,			_a   :			int=0.0    ,			_a   :			List[str]=0.02    ,			_a   :			Tuple=1e-12    ,			_a   :			int=384    ,			_a   :			Any=32    ,			_a   :			Optional[int]=3    ,			_a   :			Any=True    ,			_a   :			Union[str, Any]=-1    ,			_a   :			int=False    ,			_a   :			int=-1    ,			**_a   :			Tuple    ,			)      ->      Any:
    super().__init__(tie_word_embeddings=_a    ,			**_a     )

    __lowerCamelCase : List[Any]					 =				vocab_size
    __lowerCamelCase : int					 =				type_vocab_size
    __lowerCamelCase : Tuple					 =				modality_type_vocab_size
    __lowerCamelCase : Any					 =				max_position_embeddings

    __lowerCamelCase : List[str]					 =				hidden_size
    __lowerCamelCase : List[Any]					 =				num_hidden_layers
    __lowerCamelCase : Dict					 =				num_attention_heads
    __lowerCamelCase : Optional[int]					 =				intermediate_size
    __lowerCamelCase : Any					 =				hidden_act
    __lowerCamelCase : str					 =				hidden_dropout_prob
    __lowerCamelCase : List[Any]					 =				attention_probs_dropout_prob
    __lowerCamelCase : Any					 =				initializer_range
    __lowerCamelCase : int					 =				layer_norm_eps

    __lowerCamelCase : Optional[int]					 =				image_size
    __lowerCamelCase : Optional[Any]					 =				patch_size
    __lowerCamelCase : List[Any]					 =				num_channels
    __lowerCamelCase : List[str]					 =				qkv_bias
    __lowerCamelCase : Dict					 =				max_image_length
    __lowerCamelCase : Union[str, Any]					 =				num_images











'''simple docstring'''





from __future__ import annotations

# Define the Gravitational Constant G and the function
_UpperCamelCase							       =		6.6_743e-11  # unit of G : m^3 * kg^-1 * s^-2

def  a_  (							_lowerCAmelCase ,_lowerCAmelCase ,_lowerCAmelCase ,_lowerCAmelCase )   ->   dict[str, float]:
  __lowerCamelCase : Dict					 =				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:
    __lowerCamelCase : Optional[Any]					 =				GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
    return {"force": force}
  elif mass_a == 0:
    __lowerCamelCase : Tuple					 =				(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
    return {"mass_1": mass_a}
  elif mass_a == 0:
    __lowerCamelCase : str					 =				(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
    return {"mass_2": mass_a}
  elif distance == 0:
    __lowerCamelCase : int					 =				(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()






