diff --git a/tests/st/hypermap/test_hypermap.py b/tests/st/hypermap/test_hypermap.py index 419f7eaf228..ef94f06544a 100644 --- a/tests/st/hypermap/test_hypermap.py +++ b/tests/st/hypermap/test_hypermap.py @@ -32,6 +32,11 @@ double_elements_fg = C.MultitypeFuncGraph("double_elements_fg") def double_elements_fg_for_tensor_tuple(x, y): return P.Tile()(x, y) +@double_elements_fg.register("Tensor", "List") +def double_elements_fg_for_tensor_list(x, y): + return x + y[0] + + class HyperMapNet(nn.Cell): def __init__(self, fg): super(HyperMapNet, self).__init__() @@ -47,7 +52,7 @@ class HyperMapNet(nn.Cell): @pytest.mark.platform_x86_ascend_training @pytest.mark.platform_arm_ascend_training @pytest.mark.env_onecard -def test_single_element_hypermap(): +def test_single_element_hypermap_with_tensor_input(): """ Feature: HyperMap Description: Test whether the HyperMap with single tensor input can run successfully. @@ -70,7 +75,7 @@ def test_single_element_hypermap(): @pytest.mark.platform_x86_ascend_training @pytest.mark.platform_arm_ascend_training @pytest.mark.env_onecard -def test_double_elements_hypermap(): +def test_double_elements_hypermap_tensor_tuple_inputs(): """ Feature: HyperMap Description: Test whether the HyperMap with tensor and tuple inputs can run successfully. @@ -88,3 +93,87 @@ def test_double_elements_hypermap(): assert isinstance(output[1], Tensor) assert np.allclose(output[0].asnumpy(), expect_output_1) assert np.allclose(output[1].asnumpy(), expect_output_2) + + +@pytest.mark.level0 +@pytest.mark.platform_x86_ascend_training +@pytest.mark.platform_arm_ascend_training +@pytest.mark.env_onecard +def test_double_elements_hypermap_tensor_list_inputs(): + """ + Feature: HyperMap + Description: Test whether the HyperMap with tensor and list inputs can run successfully. + Expectation: success. + """ + x = (Tensor(np.array([1, 2, 3]), mstype.float32), Tensor(np.array([4, 5, 6]), mstype.float32)) + y = ([1, 2], [2, 1]) + common_map = HyperMapNet(double_elements_fg) + output = common_map((x, y)) + expect_output_1 = np.array([2.0, 3.0, 4.0]) + expect_output_2 = np.array([6.0, 7.0, 8.0]) + assert isinstance(output, tuple) + assert len(output) == 2 + assert isinstance(output[0], Tensor) + assert isinstance(output[1], Tensor) + assert np.allclose(output[0].asnumpy(), expect_output_1) + assert np.allclose(output[1].asnumpy(), expect_output_2) + + +@pytest.mark.level0 +@pytest.mark.platform_x86_ascend_training +@pytest.mark.platform_arm_ascend_training +@pytest.mark.env_onecard +def test_doubel_elements_hypermap_correct_mix_inputs(): + """ + Feature: HyperMap + Description: Test whether the HyperMap with mix correct inputs (Tensor + Tuple and Tensor + List) + can run successfully. + Expectation: success. + """ + x = (Tensor(np.array([1, 2, 3]), mstype.float32), Tensor(np.array([4, 5, 6]), mstype.float32)) + y = ((1, 2), [2, 1]) + common_map = HyperMapNet(double_elements_fg) + output = common_map((x, y)) + expect_output_1 = np.array([1.0, 2.0, 3.0, 1.0, 2.0, 3.0]) + expect_output_2 = np.array([6.0, 7.0, 8.0]) + assert isinstance(output, tuple) + assert len(output) == 2 + assert isinstance(output[0], Tensor) + assert isinstance(output[1], Tensor) + assert np.allclose(output[0].asnumpy(), expect_output_1) + assert np.allclose(output[1].asnumpy(), expect_output_2) + + + +@pytest.mark.level0 +@pytest.mark.platform_x86_ascend_training +@pytest.mark.platform_arm_ascend_training +@pytest.mark.env_onecard +def test_double_elements_hypermap_inputs_length_mismatch(): + """ + Feature: HyperMap + Description: When the inputs to hypermap have different length, error will be raised. + Expectation: error. + """ + x = (Tensor(np.array([1, 2, 3]), mstype.float32), Tensor(np.array([4, 5, 6]), mstype.float32)) + y = ((1, 2), (2, 1), (5, 6)) + common_map = HyperMapNet(double_elements_fg) + with pytest.raises(Exception, match="The length of tuples in HyperMap must be the same"): + common_map((x, y)) + + +@pytest.mark.level0 +@pytest.mark.platform_x86_ascend_training +@pytest.mark.platform_arm_ascend_training +@pytest.mark.env_onecard +def test_double_elements_hypermap_inconsistent_inputs(): + """ + Feature: HyperMap + Description: When the inputs to hypermap is inconsistent, error will be raised. + Expectation: error. + """ + x = (Tensor(np.array([1, 2, 3]), mstype.float32), Tensor(np.array([4, 5, 6]), mstype.float32)) + y = [(1, 2), (2, 1)] + common_map = HyperMapNet(double_elements_fg) + with pytest.raises(Exception, match="the types of arguments in HyperMap must be consistent"): + common_map((x, y))