(self, dev)
| 152 | self._softmax_helper(gpu_dev) |
| 153 | |
| 154 | def _sigmoid_helper(self, dev): |
| 155 | X = np.array([[-1, 0, 1]]).astype(np.float32) |
| 156 | x = tensor.from_numpy(X) |
| 157 | x.to_device(dev) |
| 158 | y = autograd.Sigmoid()(x)[0] |
| 159 | |
| 160 | # frontend |
| 161 | model = sonnx.to_onnx([x], [y]) |
| 162 | # print('The model is:\n{}'.format(model)) |
| 163 | |
| 164 | # backend |
| 165 | sg_ir = sonnx.prepare(model, device=dev) |
| 166 | sg_ir.is_graph = True |
| 167 | y_t = sg_ir.run([x]) |
| 168 | np.testing.assert_array_almost_equal(tensor.to_numpy(y), |
| 169 | tensor.to_numpy(y_t[0]), |
| 170 | decimal=5) |
| 171 | |
| 172 | def test_sigmoid_cpu(self): |
| 173 | self._sigmoid_helper(cpu_dev) |
no test coverage detected