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YingChen1996Ying Chen
YingChen1996
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Ying Chen
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Enable test_command_job_with_invalid_mode_type_in_pipeline_deserialize (Azure#27662)
* enable test * format * format * update Co-authored-by: Ying Chen <2601502859@qq.com>
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-33
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‎sdk/ml/azure-ai-ml/tests/pipeline_job/unittests/test_pipeline_job_entity.py‎

Lines changed: 5 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -194,8 +194,9 @@ def test_invalid_pipeline_jobs_descerialize(self, invalid_pipeline_job_without_j
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pipeline = load_pipeline_entity_from_rest_json(job_dict)
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assert pipeline.jobs == {}
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@pytest.mark.skip("azure.ai.ml.exceptions.ValidationException: Job input type None is not supported as job input.")
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def test_command_job_with_invalid_mode_type_in_pipeline_deserialize(self):
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# this json file is to test whether the client can handle the dirty data of node type/mode of the originally
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# submitted job due to API switching
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rest_job_file = "./tests/test_configs/pipeline_jobs/invalid/with_invalid_job_input_type_mode.json"
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with open(rest_job_file, "r") as f:
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job_dict = yaml.safe_load(f)
@@ -206,16 +207,17 @@ def test_command_job_with_invalid_mode_type_in_pipeline_deserialize(self):
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"hello_python_world_job": {
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"inputs": {
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"sample_input_data": {
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'mode': "ro_mount",
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"type": "uri_folder",
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"path": "azureml://datastores/workspaceblobstore/paths/LocalUpload/553d1a28-7933-4017-8321-96c2a9f1fc44/data/",
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'path': "azureml://datastores/workspaceblobstore/paths/LocalUpload/22fd2a62-9759-4843-ab92-5bd79c35f6f0/data/",
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},
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"sample_input_string": {
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"mode": "ro_mount",
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"path": "${{parent.inputs.pipeline_sample_input_string}}",
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},
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},
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"outputs": {"sample_output_data": "${{parent.outputs.pipeline_sample_output_data}}"},
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"component": "azureml:/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/sdk/providers/Microsoft.MachineLearningServices/workspaces/sdk-master/components/azureml_anonymous/versions/6ffc3ff9-8801-4cc4-9285-9f8052b946fe",
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'component': "azureml:/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/chenyin-test-eastus/providers/Microsoft.MachineLearningServices/workspaces/sdk_vnext_cli/components/azureml_anonymous/versions/9904ff48-9cb2-4733-ad1c-eb1eb9940a19",
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"type": "command",
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"compute": "azureml:cpu-cluster",
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}

‎sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/invalid/with_invalid_job_input_type_mode.json‎

Lines changed: 27 additions & 30 deletions
Original file line numberDiff line numberDiff line change
@@ -1,49 +1,49 @@
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{
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"id": "/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/sdk/providers/Microsoft.MachineLearningServices/workspaces/sdk-master/jobs/test_580619710376",
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"name": "test_580619710376",
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"id": "/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/chenyin-test-eastus/providers/Microsoft.MachineLearningServices/workspaces/sdk_vnext_cli/jobs/test_240010912529",
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"name": "test_240010912529",
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"type": "Microsoft.MachineLearningServices/workspaces/jobs",
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"system_data": {
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"created_by": "Ying Chen",
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"created_by_type": "User",
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"created_at": "2022-09-06T07:01:37.065408Z"
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"created_at": "2022-11-23T09:27:21.69252Z",
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},
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"properties": {
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"description": "Example of using data in a local folder as pipeline input",
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"properties": {
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"mlflow.source.git.repoURL": "msdata@vs-ssh.visualstudio.com:v3/msdata/Vienna/sdk-cli-v2",
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"mlflow.source.git.branch": "chenyin/parse_job_none",
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"mlflow.source.git.commit": "93afd7f355cc878a3c6348542a67ad1e62db5c49",
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"mlflow.source.git.branch": "chenyin/add_pipeline_e2e_test",
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"mlflow.source.git.commit": "a0802beac4bfc4a23eea2f9e820f067c186d6499",
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"azureml.git.dirty": "True",
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"azureml.DevPlatv2": "true",
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"azureml.runsource": "azureml.PipelineRun",
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"runSource": "MFE",
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"runType": "HTTP",
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"azureml.parameters": "{'pipeline_sample_input_string':'Hello_Pipeline_World'}",
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"azureml.parameters": '{"pipeline_sample_input_string":"Hello_Pipeline_World"}',
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"azureml.continue_on_step_failure": "False",
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"azureml.continue_on_failed_optional_input": "True",
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"azureml.defaultDataStoreName": "workspaceblobstore",
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"azureml.pipelineComponent": "pipelinerun"
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"azureml.pipelineComponent": "pipelinerun",
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},
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"tags": {},
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"display_name": "4a_local_data_input",
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"experiment_name": "azure-ai-ml",
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"is_archived": false,
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"experiment_name": "sdk-cli-v2",
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"is_archived": False,
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"job_type": "Pipeline",
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"services": {
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"Tracking": {
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"endpoint": "azureml://master.api.azureml-test.ms/mlflow/v1.0/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/sdk/providers/Microsoft.MachineLearningServices/workspaces/sdk-master?",
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"job_service_type": "Tracking"
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"endpoint": "azureml://eastus.api.azureml.ms/mlflow/v1.0/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/chenyin-test-eastus/providers/Microsoft.MachineLearningServices/workspaces/sdk_vnext_cli?",
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"job_service_type": "Tracking",
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},
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"Studio": {
38-
"endpoint": "https://ml.azure.com/runs/test_580619710376?wsid=/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourcegroups/sdk/workspaces/sdk-master",
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"job_service_type": "Studio"
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}
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"endpoint": "https://ml.azure.com/runs/test_240010912529?wsid=/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourcegroups/chenyin-test-eastus/workspaces/sdk_vnext_cli",
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"job_service_type": "Studio",
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},
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},
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"status": "Preparing",
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"inputs": {
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"pipeline_sample_input_string": {
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"job_input_type": "Literal",
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"value": "Hello_Pipeline_World"
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"job_input_type": "literal",
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"value": "Hello_Pipeline_World",
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}
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},
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"jobs": {
@@ -53,39 +53,36 @@
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"limits": null,
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"environment_variables": {},
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"name": "hello_python_world_job",
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"type": "command",
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"display_name": null,
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"tags": {},
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"computeId": "/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/sdk/providers/Microsoft.MachineLearningServices/workspaces/sdk-master/computes/cpu-cluster",
58+
"computeId": "/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/chenyin-test-eastus/providers/Microsoft.MachineLearningServices/workspaces/sdk_vnext_cli/computes/cpu-cluster",
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"inputs": {
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"sample_input_string": {
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"job_input_type": "Literal",
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"value": "${{parent.inputs.pipeline_sample_input_string}}",
64-
"mode": "RoMount"
63+
"mode": "RoMount",
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},
6665
"sample_input_data": {
67-
"uri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/553d1a28-7933-4017-8321-96c2a9f1fc44/data/",
68-
"job_input_type": "UriFolder"
69-
}
66+
"mode": "ReadOnlyMount",
67+
"uri": "azureml://datastores/workspaceblobstore/paths/LocalUpload/22fd2a62-9759-4843-ab92-5bd79c35f6f0/data/",
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"job_input_type": "UriFolder",
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},
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},
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"outputs": {
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"sample_output_data": {
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"value": "${{parent.outputs.pipeline_sample_output_data}}",
74-
"type": "Literal"
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"type": "Literal",
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}
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},
77-
"_source": "YAML.JOB",
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"componentId": "/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/sdk/providers/Microsoft.MachineLearningServices/workspaces/sdk-master/components/azureml_anonymous/versions/6ffc3ff9-8801-4cc4-9285-9f8052b946fe"
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"componentId": "/subscriptions/96aede12-2f73-41cb-b983-6d11a904839b/resourceGroups/chenyin-test-eastus/providers/Microsoft.MachineLearningServices/workspaces/sdk_vnext_cli/components/azureml_anonymous/versions/9904ff48-9cb2-4733-ad1c-eb1eb9940a19",
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}
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},
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"outputs": {
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"pipeline_sample_output_data": {
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"mode": "Upload",
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"job_output_type": "UriFolder"
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"job_output_type": "uri_folder",
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}
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},
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"settings": {
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"_source": "YAML.JOB"
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}
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}
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"settings": {},
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},
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}

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