'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.'

def backward(self, out_grads=None):

    assert (out_grads is None), 'For    a    loss    module,    out_grads    should    be    None'
    assert self.for_training
    self._backward_impl()
