sxjscience commented on issue #10002: General support of OPs for second-order 
   @lightingghost  Borrow the discussion in here
   import mxnet.ndarray as nd
   from mxnet import autograd
   x = nd.array([3.0])
   with autograd.record():
       y = x**2
       y_grad = autograd.grad(y, x, create_graph=True, retain_graph=True)[0]
       z = y_grad ** 2
   MXNetError: [12:44:29] src/pass/ Operator 
_backward_power_scalar is non-differentiable because it didn't register 
FGradient attribute.

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