wkcn commented on issue #18539:
URL:
https://github.com/apache/incubator-mxnet/issues/18539#issuecomment-643003657
Another solution: add `mx.sym.MakeLoss`
```python
import mxnet as mx
a = mx.sym.Variable('a')
b = mx.sym.Variable('b')
# c is not a loss function symbol
c = mx.sym.MakeLoss(2 * a + b)
args = {'a': mx.nd.array([1,2]), 'b':mx.nd.array([2,3])}
args_grad = {'a': mx.nd.zeros((2)), 'b': mx.nd.zeros((2))}
texec = c.bind(ctx=mx.cpu(), args=args, args_grad=args_grad)
out = texec.forward(is_train=True)[0].copy()
print(out.asnumpy())
# answer [ 4. 7.]
texec.backward()
print(texec.grad_arrays[0].asnumpy())
# answer[ 2. 2.]
print(texec.grad_arrays[1].asnumpy())
# answer [ 1. 1.]
```
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