(self, dev)
| 1154 | self._Less_helper(gpu_dev) |
| 1155 | |
| 1156 | def _Sub_helper(self, dev): |
| 1157 | X0 = np.array([7, -5, 0.2, -0.1, 0.3, 4]).reshape(3, |
| 1158 | 2).astype(np.float32) |
| 1159 | X1 = np.array([0.6, -1.3, 0.1, -0.1, 0.4, |
| 1160 | 0.3]).reshape(3, 2).astype(np.float32) |
| 1161 | XT = np.subtract(X0, X1) |
| 1162 | |
| 1163 | DY = np.ones((3, 2), dtype=np.float32) |
| 1164 | x0 = tensor.from_numpy(X0) |
| 1165 | x1 = tensor.from_numpy(X1) |
| 1166 | dy = tensor.from_numpy(DY) |
| 1167 | x0.to_device(dev) |
| 1168 | x1.to_device(dev) |
| 1169 | dy.to_device(dev) |
| 1170 | |
| 1171 | result = autograd.sub(x0, x1) |
| 1172 | dx0, dx1 = result.creator.backward(dy.data) |
| 1173 | |
| 1174 | DX0 = np.multiply(DY, 1.0) |
| 1175 | DX1 = np.multiply(DY, -1.0) |
| 1176 | |
| 1177 | np.testing.assert_array_almost_equal(tensor.to_numpy(result), |
| 1178 | XT, |
| 1179 | decimal=5) |
| 1180 | np.testing.assert_array_almost_equal(tensor.to_numpy( |
| 1181 | tensor.from_raw_tensor(dx0)), |
| 1182 | DX0, |
| 1183 | decimal=5) |
| 1184 | np.testing.assert_array_almost_equal(tensor.to_numpy( |
| 1185 | tensor.from_raw_tensor(dx1)), |
| 1186 | DX1, |
| 1187 | decimal=5) |
| 1188 | |
| 1189 | def test_Sub_cpu(self): |
| 1190 | self._Sub_helper(cpu_dev) |
no test coverage detected