(self, dev)
| 127 | self._avg_pool_helper(gpu_dev) |
| 128 | |
| 129 | def _softmax_helper(self, dev): |
| 130 | X = np.array([[-1, 0, 1]]).astype(np.float32) |
| 131 | x = tensor.from_numpy(X) |
| 132 | x.to_device(dev) |
| 133 | y = autograd.SoftMax()(x)[0] |
| 134 | |
| 135 | # frontend |
| 136 | model = sonnx.to_onnx([x], [y]) |
| 137 | # print('The model is:\n{}'.format(model)) |
| 138 | |
| 139 | # backend |
| 140 | sg_ir = sonnx.prepare(model, device=dev) |
| 141 | sg_ir.is_graph = True |
| 142 | y_t = sg_ir.run([x]) |
| 143 | np.testing.assert_array_almost_equal(tensor.to_numpy(y), |
| 144 | tensor.to_numpy(y_t[0]), |
| 145 | decimal=5) |
| 146 | |
| 147 | def test_softmax_cpu(self): |
| 148 | self._softmax_helper(cpu_dev) |
no test coverage detected