fa961f2290c3144f1c5a5c9b8a484610ab835032,art/defences/spatial_smoothing.py,SpatialSmoothing,__call__,#SpatialSmoothing#Any#Any#,58

Before Change

        :return: Smoothed sample
        :rtype: `np.ndarray`
        
        clip_values = (0, 1)

        assert self.channel_index < len(x.shape)
        size = [1] + [self.window_size] * (len(x.shape) - 1)
        size[self.channel_index] = 1
        size = tuple(size)

        result = ndimage.filters.median_filter(x, size=size, mode="reflect")
        result = np.clip(result, clip_values[0], clip_values[1])

        return result.astype(NUMPY_DTYPE), y

    def estimate_gradient(self, x, grad):

After Change

        :return: Smoothed sample
        :rtype: `np.ndarray`
        
        if len(x.shape) == 2:
            raise ValueError("Feature vectors detected. Smoothing can only be applied to data with spatial "
                             "dimensions.")
        if self.channel_index >= len(x.shape):
            raise ValueError("Channel index does not match input shape.")

        size = [1] + [self.window_size] * (len(x.shape) - 1)
        size[self.channel_index] = 1
        size = tuple(size)

        result = ndimage.filters.median_filter(x, size=size, mode="reflect")
        if hasattr(self, "clip_values") and self.clip_values is not None:
            np.clip(result, self.clip_values[0], self.clip_values[1], out=result)

        return result.astype(NUMPY_DTYPE), y

    def estimate_gradient(self, x, grad):
        return grad

Instances