

"""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						(							_UpperCAmelCase   ,							_UpperCAmelCase			):







    """simple docstring"""





    @register_to_config
    def __init__(				self			:	str,lowercase_			:	Tuple = 7_6_8,)->   Dict:





        '''simple docstring'''







        super().__init__()

        A__   				=       nn.Parameter(torch.zeros(1,lowerCamelCase_		)		)
        A__   				=       nn.Parameter(torch.ones(1,lowerCamelCase_		)		)


    def 						snake_case__					(				self			:	Union[str, Any],lowercase_			:	Union[str, Any] = None,lowercase_			:	Any = None,)->   Union[str, Any]:





        '''simple docstring'''







        A__   				=       nn.Parameter(self.mean.to(lowerCamelCase_		).to(lowerCamelCase_		)		)
        A__   				=       nn.Parameter(self.std.to(lowerCamelCase_		).to(lowerCamelCase_		)		)
        return self


    def 						snake_case__					(				self			:	Optional[Any],lowercase_			:	Optional[Any]		)->   int:





        '''simple docstring'''







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


    def 						snake_case__					(				self			:	int,lowercase_			:	Optional[Any]		)->   int:





        '''simple docstring'''







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




def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     int = 1000				)							->				int:





    '''simple docstring'''






    A__   				=       3
    A__   				=       0
    while a < n:
        if a % 3 == 0 or a % 5 == 0:
            result += a
        elif a % 15 == 0:
            result -= a
        a += 1
    return result


if __name__ == "__main__":
     print(f"""{solution() = }""")

