'''simple docstring'''


def  _lowerCamelCase   (				lowerCamelCase_ :							Optional[Any]       ):



     """simple docstring"""





     if a < 0:
          raise ValueError('Input value must be a positive integer'       )
     elif isinstance(_lowerCAmelCase     ,					_lowerCAmelCase       ):
          raise TypeError('Input value must be a \'int\' type'       )
     return bin(_lowerCAmelCase       ).count('1'       )


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 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_						,     lowerCamelCase_	):







  '''simple docstring'''






  @register_to_config
  def __init__(			self				,		snake_case_ = 7_6_8				,		):




       '''simple docstring'''

       super().__init__()

       UpperCAmelCase_							:       int       =				nn.Parameter(torch.zeros(1				,		snake_case_						)						)
       UpperCAmelCase_							:       str       =				nn.Parameter(torch.ones(1				,		snake_case_						)						)


  def _UpperCamelCase					(			self				,		snake_case_ = None				,		snake_case_ = None				,		):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				nn.Parameter(self.mean.to(snake_case_						).to(snake_case_						)						)
       UpperCAmelCase_							:       Tuple       =				nn.Parameter(self.std.to(snake_case_						).to(snake_case_						)						)
       return self


  def _UpperCamelCase					(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Dict       =				(embeds - self.mean) * 1.0 / self.std
       return embeds






  def _UpperCamelCase					(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[Any]       =				(embeds * self.std) + self.mean
       return embeds






