class_docstr: Compute the Total Variation according to [1].
  
  Shape:
      - Input: :math:`(*, H, W)`.
      - Output: :math:`(*,)`.
  
  Examples:
      >>> tv = TotalVariation()
      >>> output = tv(torch.ones((2, 3, 4, 4), requires_grad=True))
      >>> output.data
      tensor([[0., 0., 0.],
              [0., 0., 0.]])
      >>> output.sum().backward()  # grad can be implicitly created only for scalar outputs
  
  Reference:
      [1] https://en.wikipedia.org/wiki/Total_variation
code: def forward(self, img: Tensor) -> Tensor:
      return total_variation(img)
  
imports: from __future__ import annotations
  from kornia.core import Module, Tensor
  from kornia.core.check import KORNIA_CHECK, KORNIA_CHECK_SHAPE
label_desc: Use image node_id 1 for calling the TotalVariation obj's underlying member method code with example usage: obj.forward(img) and returns: total_variation