(self, dev)
| 1696 | self._reduceSum_helper(gpu_dev) |
| 1697 | |
| 1698 | def _reduceMean_helper(self, dev): |
| 1699 | X = np.random.randn(3, 4, 5).astype(np.float32) |
| 1700 | |
| 1701 | x = tensor.from_numpy(X) |
| 1702 | x.to_device(dev) |
| 1703 | y = autograd.reduce_mean(x, None, 1) |
| 1704 | |
| 1705 | # frontend |
| 1706 | model = sonnx.to_onnx([x], [y]) |
| 1707 | # print('The model is:\n{}'.format(model)) |
| 1708 | |
| 1709 | # backend |
| 1710 | sg_ir = sonnx.prepare(model, device=dev) |
| 1711 | sg_ir.is_graph = True |
| 1712 | y_t = sg_ir.run([x]) |
| 1713 | |
| 1714 | np.testing.assert_array_almost_equal( |
| 1715 | tensor.to_numpy(y).shape, |
| 1716 | tensor.to_numpy(y_t[0]).shape) |
| 1717 | |
| 1718 | def test_reduceMean_cpu(self): |
| 1719 | self._reduceMean_helper(cpu_dev) |
no test coverage detected