






from __future__ import annotations

SCREAMING_SNAKE_CASE__		:							List[str] 				=				8.988e9  # units = N * m^s * C^-2





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       ) ->			dict[str, float]:

     '''simple docstring'''
     UpperCAmelCase__      :  int				      =			abs(chargea * chargea       )

     if (force, chargea, chargea, distance).count(0       ) != 1:
          raise ValueError("""One and only one argument must be 0"""       )
     if distance < 0:
          raise ValueError("""Distance cannot be negative"""       )
     if force == 0:
          UpperCAmelCase__      :  int				      =			COULOMBS_CONSTANT * charge_product / (distance**2)
          return {"force": force}
     elif chargea == 0:
          UpperCAmelCase__      :  str				      =			abs(__lowerCamelCase       ) * (distance**2) / (COULOMBS_CONSTANT * chargea)
          return {"charge1": chargea}
     elif chargea == 0:
          UpperCAmelCase__      :  Union[str, Any]				      =			abs(__lowerCamelCase       ) * (distance**2) / (COULOMBS_CONSTANT * chargea)
          return {"charge2": chargea}
     elif distance == 0:
          UpperCAmelCase__      :  Optional[Any]				      =			(COULOMBS_CONSTANT * charge_product / abs(__lowerCamelCase       )) ** 0.5
          return {"distance": distance}
     raise ValueError("""Exactly one argument must be 0"""       )


if __name__ == "__main__":
      import doctest

      doctest.testmod()













'''simple docstring'''

from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin






class   UpperCAmelCase      (			UpperCamelCase__     ,			UpperCamelCase__							):
 @register_to_config
 def __init__(							self :List[str]		,			lowercase_ :int = 7_68		,			)->				str:
     super().__init__()

     A__							=     nn.Parameter(torch.zeros(1		,			lowercase_				)				)
     A__							=     nn.Parameter(torch.ones(1		,			lowercase_				)				)
 def 	UpperCAmelCase_				(							self :List[Any]		,			lowercase_ :Optional[Union[str, torch.device]] = None		,			lowercase_ :Optional[torch.dtype] = None		,			)->				Tuple:
     A__							=     nn.Parameter(self.mean.to(lowercase_				).to(lowercase_				)				)
     A__							=     nn.Parameter(self.std.to(lowercase_				).to(lowercase_				)				)
     return self
 def 	UpperCAmelCase_				(							self :Optional[int]		,			lowercase_ :str				)->				Union[str, Any]:
     A__							=     (embeds - self.mean) * 1.0 / self.std
     return embeds



 def 	UpperCAmelCase_				(							self :Any		,			lowercase_ :List[Any]				)->				Tuple:
     A__							=     (embeds * self.std) + self.mean
     return embeds



