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ZdS )	    )AnyDictOptionalTupleUnion)random_generator)IntensityAugmentationBase2D)Tensor	sharpnessc                       s   e Zd ZdZ				ddeeeeeef f dedededd	f
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ddZ  ZS )RandomSharpnessa  Sharpen given tensor image or a batch of tensor images randomly.

    .. image:: _static/img/RandomSharpness.png

    Args:
        p: probability of applying the transformation.
        sharpness: factor of sharpness strength. Must be above 0.
        same_on_batch: apply the same transformation across the batch.
        keepdim: whether to keep the output shape the same as input (True) or broadcast it
                 to the batch form (False).

    Shape:
        - Input: :math:`(C, H, W)` or :math:`(B, C, H, W)`, Optional: :math:`(B, 3, 3)`
        - Output: :math:`(B, C, H, W)`

    .. note::
        This function internally uses :func:`kornia.enhance.sharpness`.

    Examples:
        >>> rng = torch.manual_seed(0)
        >>> input = torch.rand(1, 1, 5, 5)
        >>> sharpness = RandomSharpness(1., p=1.)
        >>> sharpness(input)
        tensor([[[[0.4963, 0.7682, 0.0885, 0.1320, 0.3074],
                  [0.6341, 0.4810, 0.7367, 0.4177, 0.6323],
                  [0.3489, 0.4428, 0.1562, 0.2443, 0.2939],
                  [0.5185, 0.6462, 0.7050, 0.2288, 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 = RandomSharpness(1., p=1.)
        >>> (aug(input) == aug(input, params=aug._params)).all()
        tensor(True)

          ?Fr   same_on_batchpkeepdimreturnNc                    s2   t  j|||d t|dddtdff| _d S )N)r   r   r   r   g        r   inf)super__init__rgPlainUniformGeneratorfloat_param_generator)selfr   r   r   r   	__class__ _/home/ubuntu/.local/lib/python3.10/site-packages/kornia/augmentation/_2d/intensity/sharpness.pyr   @   s    zRandomSharpness.__init__inputparamsflags	transformc                 C   s   |d }t ||S )Nr   r
   )r   r   r   r    r!   factorr   r   r   apply_transformJ   s   
zRandomSharpness.apply_transform)r   Fr   F)N)__name__
__module____qualname____doc__r   r	   r   r   boolr   r   strr   r   r#   __classcell__r   r   r   r   r      s:    '

r   N)typingr   r   r   r   r   kornia.augmentationr   r   &kornia.augmentation._2d.intensity.baser   kornia.corer	   kornia.enhancer   r   r   r   r   r   <module>   s   