Note that when "strict" is "False", the result can not require
        gradients or be disconnected from the inputs. Defaults to
        "False".
  * **strict** (*bool**, **optional*) -- If "True", an error will
    be raised when we detect that there exists an input such that
    all the outputs are independent of it. If "False", we return a
    Tensor of zeros as the vhp for said inputs, which is the
    expected mathematical value. Defaults to "False".

Returns:
      tuple with:
         func_output (tuple of Tensors or Tensor): output of
         "func(inputs)"
     vhp (tuple of Tensors or Tensor): result of the dot product
     with the same shape as the inputs.

Return type:
      output (tuple)
-[ Example ]-



def pow_reducer(x):
   ...     return x.pow(3).sum()
inputs = torch.rand(2, 2)
v = torch.ones(2, 2)
vhp(pow_reducer, inputs, v)
   (tensor(0.5591),
    tensor([[1.0689, 1.2431],
            [3.0989, 4.4456]]))


