'Backward computation.
Parameters
out_grads : NDArray or list of NDArray, optional
Gradient on the outputs to be propagated back.
This parameter is only needed when bind is called
on outputs that are not a loss function.
Examples
>>> # An example of backward computation.
>>> mod.backward()
>>> print mod.get_input_grads()[0].asnumpy()
[[[  1.10182791e-05   5.12257748e-06   4.01927764e-06   8.32566820e-06
-1.59775993e-06   7.24269375e-06   7.28067835e-06  -1.65902311e-05
5.46342608e-06   8.44196393e-07]'

def backward(self, out_grads=None):

    raise NotImplementedError()
