(self, dev)
| 1616 | self._reciprocal_helper(gpu_dev) |
| 1617 | |
| 1618 | def _constantOfShape_helper(self, dev): |
| 1619 | X = np.array([4, 3, 2]).astype(np.int64) |
| 1620 | x = tensor.from_numpy(X) |
| 1621 | x.to_device(cpu_dev) |
| 1622 | |
| 1623 | y = autograd.constant_of_shape(x, 1.) |
| 1624 | # frontend |
| 1625 | model = sonnx.to_onnx([x], [y]) |
| 1626 | # print('The model is:\n{}'.format(model)) |
| 1627 | |
| 1628 | # backend |
| 1629 | sg_ir = sonnx.prepare(model, device=dev, init_inputs=[X]) |
| 1630 | sg_ir.is_graph = True |
| 1631 | y_t = sg_ir.run([x]) |
| 1632 | |
| 1633 | np.testing.assert_array_almost_equal(tensor.to_numpy(y), |
| 1634 | tensor.to_numpy(y_t[0]), |
| 1635 | decimal=5) |
| 1636 | |
| 1637 | def test_constantOfShape_cpu(self): |
| 1638 | self._constantOfShape_helper(cpu_dev) |
no test coverage detected