def _pad(self, x):
        """Pad the input tensor to align with kernel size.

        Args:
            x (torch.Tensor): Input tensor of shape (batch, channels, height, width).

        Returns:
            tuple: Padded tensor and padding values.
        """
        b, c, h, w = x.shape
        k1, k2 = self.kernel_size
        mod_pad_h = (k1 - h % k1) % k1
        mod_pad_w = (k2 - w % k2) % k2
        pad = (mod_pad_w // 2, mod_pad_w - mod_pad_w // 2, mod_pad_h // 2, mod_pad_h - mod_pad_h // 2)
        x = F.pad(x, pad, "reflect")
        return x, pad
Pad the input tensor to align with kernel size.

        Args:
            x (torch.Tensor): Input tensor of shape (batch, channels, height, width).

        Returns:
            tuple: Padded tensor and padding values.
        
examples/community/pipeline_faithdiff_stable_diffusion_xl.py