kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337794186 @ZiyueHuang `a`s first dimension is 4, and slicing it like `a[0:4]` is absolutely valid and I didn't care about effectiveness here. But after you asked, I tried different expressions. I tried different sizes of `a` (for example, `a = mx.nd.array([ [ 1, 2, 3, 4] ])` and slicing it in the expression as `a[0]`). None of that has worked. I still see the same error every time I use slicing. `da_sym.list_arguments()` returns `['', 'var0']`. One must be the head gradient for the chain rule and another one is a placeholder the for variable `a`. That's why I used such arguments. Which is which I determined experimentally, since both have different shapes, and I could easilly check the result of `executor.forward()` knowing derivative `db / da = 4 * a`.
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