| @@ -18,7 +18,6 @@ from mindspore import nn, context | |||
| from mindspore import ops as P | |||
| from mindspore.train import DatasetHelper, connect_network_with_dataset | |||
| import mindspore.dataset as ds | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") | |||
| def _exec_preprocess(network, is_train, dataset, dataset_sink_mode, sink_size=1, epoch_num=1, dataset_helper=None): | |||
| @@ -77,7 +76,13 @@ class Net(nn.Cell): | |||
| @pytest.mark.platform_arm_ascend_training | |||
| @pytest.mark.platform_x86_ascend_training | |||
| @pytest.mark.env_onecard | |||
| def test_getnext_dynamic_pipeline(): | |||
| def test_getnext_dynamic_pipeline_ascend(): | |||
| """ | |||
| Feature: sink one step of dynamic data sink. | |||
| Description: datasets with dynamic shape as input. | |||
| Expectation: success without assert exception. | |||
| """ | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") | |||
| network = Net() | |||
| dataset = ds.GeneratorDataset( | |||
| dataset_generator, ["data1", "data2", "data3", "data4", "data5"]) | |||
| @@ -86,10 +91,6 @@ def test_getnext_dynamic_pipeline(): | |||
| _eval_dataset_sink_process(network, dataset) | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_arm_ascend_training | |||
| @pytest.mark.platform_x86_ascend_training | |||
| @pytest.mark.env_onecard | |||
| def test_getnext_sink_size_dynamic_pipeline(): | |||
| """ | |||
| Feature: arbitrary sink size of dynamic data sink. | |||
| @@ -110,3 +111,29 @@ def test_getnext_sink_size_dynamic_pipeline(): | |||
| last_inputs = data_item.items() | |||
| for output, (_, last_input) in zip(outputs, last_inputs): | |||
| assert output.shape == last_input.shape | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_arm_ascend_training | |||
| @pytest.mark.platform_x86_ascend_training | |||
| @pytest.mark.env_onecard | |||
| def test_getnext_sink_size_dynamic_pipeline_ascend(): | |||
| """ | |||
| Feature: arbitrary sink size of dynamic data sink. | |||
| Description: datasets with dynamic shape as input. | |||
| Expectation: success without assert exception. | |||
| """ | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") | |||
| test_getnext_sink_size_dynamic_pipeline() | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_x86_gpu_training | |||
| @pytest.mark.env_onecard | |||
| def test_getnext_sink_size_dynamic_pipeline_gpu(): | |||
| """ | |||
| Feature: arbitrary sink size of dynamic data sink. | |||
| Description: datasets with dynamic shape as input. | |||
| Expectation: success without assert exception. | |||
| """ | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="GPU") | |||
| test_getnext_sink_size_dynamic_pipeline() | |||