(self)
| 19 | self.assertListEqual(x.sum().gradient(w)[0].tolist(), [0.0, 0.0, 0.0]) |
| 20 | |
| 21 | def test_with_custom_gradient(self): |
| 22 | x = Tensor([1.0, 2.0, 3.0]) |
| 23 | z = (x * x).sum() |
| 24 | dx = z.gradient(x, gradient=Tensor([3.0]))[0] |
| 25 | self.assertListEqual(dx.tolist(), [6.0, 12.0, 18.0]) |
| 26 | |
| 27 | def test_broadcast_gradient(self): |
| 28 | x = Tensor([[1.0], [2.0], [3.0]]) |