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 G dd deZdS )    )AnyDictOptionalUnionN)Tensor)IntensityAugmentationBase2D)invertc                       s~   e Zd ZdZ				ddeeef dededed	d
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ddZ  ZS )RandomInverta?  Invert the tensor images values randomly.

    .. image:: _static/img/RandomInvert.png

    Args:
        max_val: The expected maximum value in the input tensor. The shape has to
          according to the input tensor shape, or at least has to work with broadcasting.
        same_on_batch: apply the same transformation across the batch.
        p: probability of applying the transformation.
        keepdim: whether to keep the output shape the same as input (True) or broadcast it
                 to the batch form (False).
    .. note::
        This function internally uses :func:`kornia.enhance.invert`.

    Examples:
        >>> rng = torch.manual_seed(0)
        >>> img = torch.rand(1, 1, 5, 5)
        >>> inv = RandomInvert()
        >>> inv(img)
        tensor([[[[0.4963, 0.7682, 0.0885, 0.1320, 0.3074],
                  [0.6341, 0.4901, 0.8964, 0.4556, 0.6323],
                  [0.3489, 0.4017, 0.0223, 0.1689, 0.2939],
                  [0.5185, 0.6977, 0.8000, 0.1610, 0.2823],
                  [0.6816, 0.9152, 0.3971, 0.8742, 0.4194]]]])

    To apply the exact augmenation again, you may take the advantage of the previous parameter state:
        >>> input = torch.randn(1, 3, 32, 32)
        >>> aug = RandomInvert(p=1.)
        >>> (aug(input) == aug(input, params=aug._params)).all()
        tensor(True)

          ?F      ?max_valsame_on_batchpkeepdimreturnNc                    s"   t  j||d|d d|i| _d S )Nr
   )r   r   p_batchr   r   )super__init__flags)selfr   r   r   r   	__class__ \/home/ubuntu/.local/lib/python3.10/site-packages/kornia/augmentation/_2d/intensity/invert.pyr   =   s   zRandomInvert.__init__inputparamsr   	transformc                 C   s   t |tj|d |j|jdS )Nr   )devicedtype)r   torch	as_tensorr   r   )r   r   r   r   r   r   r   r   apply_transformG   s   zRandomInvert.apply_transform)r
   Fr   F)N)__name__
__module____qualname____doc__r   floatr   boolr   r   strr   r   r!   __classcell__r   r   r   r   r	      s:    #


r	   )typingr   r   r   r   r   r   &kornia.augmentation._2d.intensity.baser   kornia.enhancer   r	   r   r   r   r   <module>   s   