def  __UpperCamelCase    (						A ,							A							):
     return [sentence[i : i + ngram_size] for i in range(len(A							) - ngram_size + 1							)]


if __name__ == "__main__":
     from doctest import testmod

     testmod()




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   (    __UpperCamelCase	, __UpperCamelCase							):






  @register_to_config
  def __init__(self   ,				SCREAMING_SNAKE_CASE_ = 768   ,				)		->      Tuple:





       '''simple docstring'''





       super().__init__()

       UpperCamelCase__										=      nn.Parameter(torch.zeros(1   ,				SCREAMING_SNAKE_CASE_	)	)
       UpperCamelCase__										=      nn.Parameter(torch.ones(1   ,				SCREAMING_SNAKE_CASE_	)	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_ = None   ,				SCREAMING_SNAKE_CASE_ = None   ,				)		->      Tuple:





       '''simple docstring'''





       UpperCamelCase__										=      nn.Parameter(self.mean.to(SCREAMING_SNAKE_CASE_	).to(SCREAMING_SNAKE_CASE_	)	)
       UpperCamelCase__										=      nn.Parameter(self.std.to(SCREAMING_SNAKE_CASE_	).to(SCREAMING_SNAKE_CASE_	)	)
       return self






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      int:





       '''simple docstring'''





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






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      int:





       '''simple docstring'''





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



