




from statistics import mean, stdev


def 							__SCREAMING_SNAKE_CASE  (			snake_case_	,    snake_case_ = 3						):

						'''simple docstring'''


						_UpperCAmelCase													=     min(_UpperCamelCase						)
						_UpperCAmelCase													=     max(_UpperCamelCase						)
						# normalize data
						return [round((x - x_min) / (x_max - x_min)	,    _UpperCamelCase						) for x in data]





def 							__SCREAMING_SNAKE_CASE  (			snake_case_	,    snake_case_ = 3						):

						'''simple docstring'''


						_UpperCAmelCase													=     mean(_UpperCamelCase						)
						_UpperCAmelCase													=     stdev(_UpperCamelCase						)
						# standardize data
						return [round((x - mu) / (sigma)	,    _UpperCamelCase						) for x in data]







'''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 							A__    (       A__     ,   A__  ):





  @register_to_config
  def __init__(		self      :	Dict							,					_a      :	int = 768							,					)	->    Union[str, Any]:





       '''simple docstring'''






       super().__init__()

       _SCREAMING_SNAKE_CASE							    =nn.Parameter(torch.zeros(1							,					_a ) )
       _SCREAMING_SNAKE_CASE							    =nn.Parameter(torch.ones(1							,					_a ) )





  def 						A  (		self      :	Tuple							,					_a      :	Optional[Union[str, torch.device]] = None							,					_a      :	Optional[torch.dtype] = None							,					)	->    List[Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =nn.Parameter(self.mean.to(_a ).to(_a ) )
       _SCREAMING_SNAKE_CASE							    =nn.Parameter(self.std.to(_a ).to(_a ) )
       return self





  def 						A  (		self      :	Tuple							,					_a      :	str )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =(embeds - self.mean) * 1.0 / self.std
       return embeds





  def 						A  (		self      :	List[str]							,					_a      :	Optional[Any] )	->    Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =(embeds * self.std) + self.mean
       return embeds
