


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							(    __lowercase					,						__lowercase):




	@register_to_config
	def __init__( self						:		Any		, _SCREAMING_SNAKE_CASE						:		int = 768		, )->	int:
			super().__init__()

			lowerCAmelCase__       :      Dict   					= nn.Parameter(torch.zeros(1		, UpperCAmelCase__		)		)
			lowerCAmelCase__       :      Any   					= nn.Parameter(torch.ones(1		, UpperCAmelCase__		)		)




	def 							UpperCAmelCase__( self						:		Any		, _SCREAMING_SNAKE_CASE						:		Optional[Union[str, torch.device]] = None		, _SCREAMING_SNAKE_CASE						:		Optional[torch.dtype] = None		, )->	Optional[Any]:
			lowerCAmelCase__       :      int   					= nn.Parameter(self.mean.to(UpperCAmelCase__		).to(UpperCAmelCase__		)		)
			lowerCAmelCase__       :      int   					= nn.Parameter(self.std.to(UpperCAmelCase__		).to(UpperCAmelCase__		)		)
			return self




	def 							UpperCAmelCase__( self						:		Any		, _SCREAMING_SNAKE_CASE						:		Any		)->	List[Any]:
			lowerCAmelCase__       :      List[Any]   					= (embeds - self.mean) * 1.0 / self.std
			return embeds




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		str		)->	Any:
			lowerCAmelCase__       :      int   					= (embeds * self.std) + self.mean
			return embeds






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		if number < 0:
				raise ValueError('''number must not be negative'''	)
		return number & (number - 1) == 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()




