Reverted file

googleapis · Apr 21, 2021 · e4be6f4 · e4be6f4
1 parent 84bf42a
commit e4be6f4
Showing 1 changed file with 0 additions and 150 deletions.
diff --git a/tests/unit/aiplatform/test_training_jobs.py b/tests/unit/aiplatform/test_training_jobs.py
@@ -3043,156 +3043,6 @@ def test_run_call_pipeline_service_create_with_tabular_dataset(
 
         assert job.state == gca_pipeline_state.PipelineState.PIPELINE_STATE_SUCCEEDED
 
-    @pytest.mark.parametrize("sync", [True, False])
-    def test_run_call_pipeline_service_create_with_tabular_dataset_without_model_display_name(
-        self,
-        mock_pipeline_service_create,
-        mock_pipeline_service_get,
-        mock_tabular_dataset,
-        mock_model_service_get,
-        sync,
-    ):
-        aiplatform.init(
-            project=_TEST_PROJECT,
-            staging_bucket=_TEST_BUCKET_NAME,
-            encryption_spec_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME,
-        )
-
-        job = training_jobs.CustomPythonPackageTrainingJob(
-            display_name=_TEST_DISPLAY_NAME,
-            python_package_gcs_uri=_TEST_OUTPUT_PYTHON_PACKAGE_PATH,
-            python_module_name=_TEST_PYTHON_MODULE_NAME,
-            container_uri=_TEST_TRAINING_CONTAINER_IMAGE,
-            model_serving_container_image_uri=_TEST_SERVING_CONTAINER_IMAGE,
-            model_serving_container_predict_route=_TEST_SERVING_CONTAINER_PREDICTION_ROUTE,
-            model_serving_container_health_route=_TEST_SERVING_CONTAINER_HEALTH_ROUTE,
-            model_serving_container_command=_TEST_MODEL_SERVING_CONTAINER_COMMAND,
-            model_serving_container_args=_TEST_MODEL_SERVING_CONTAINER_ARGS,
-            model_serving_container_environment_variables=_TEST_MODEL_SERVING_CONTAINER_ENVIRONMENT_VARIABLES,
-            model_serving_container_ports=_TEST_MODEL_SERVING_CONTAINER_PORTS,
-            model_description=_TEST_MODEL_DESCRIPTION,
-            model_instance_schema_uri=_TEST_MODEL_INSTANCE_SCHEMA_URI,
-            model_parameters_schema_uri=_TEST_MODEL_PARAMETERS_SCHEMA_URI,
-            model_prediction_schema_uri=_TEST_MODEL_PREDICTION_SCHEMA_URI,
-        )
-
-        model_from_job = job.run(
-            dataset=mock_tabular_dataset,
-            # model_display_name=_TEST_MODEL_DISPLAY_NAME,
-            base_output_dir=_TEST_BASE_OUTPUT_DIR,
-            args=_TEST_RUN_ARGS,
-            replica_count=1,
-            machine_type=_TEST_MACHINE_TYPE,
-            accelerator_type=_TEST_ACCELERATOR_TYPE,
-            accelerator_count=_TEST_ACCELERATOR_COUNT,
-            training_fraction_split=_TEST_TRAINING_FRACTION_SPLIT,
-            validation_fraction_split=_TEST_VALIDATION_FRACTION_SPLIT,
-            test_fraction_split=_TEST_TEST_FRACTION_SPLIT,
-            predefined_split_column_name=_TEST_PREDEFINED_SPLIT_COLUMN_NAME,
-            sync=sync,
-        )
-
-        if not sync:
-            model_from_job.wait()
-
-        true_args = _TEST_RUN_ARGS
-
-        true_worker_pool_spec = {
-            "replicaCount": _TEST_REPLICA_COUNT,
-            "machineSpec": {
-                "machineType": _TEST_MACHINE_TYPE,
-                "acceleratorType": _TEST_ACCELERATOR_TYPE,
-                "acceleratorCount": _TEST_ACCELERATOR_COUNT,
-            },
-            "pythonPackageSpec": {
-                "executorImageUri": _TEST_TRAINING_CONTAINER_IMAGE,
-                "pythonModule": _TEST_PYTHON_MODULE_NAME,
-                "packageUris": [_TEST_OUTPUT_PYTHON_PACKAGE_PATH],
-                "args": true_args,
-            },
-        }
-
-        true_fraction_split = gca_training_pipeline.FractionSplit(
-            training_fraction=_TEST_TRAINING_FRACTION_SPLIT,
-            validation_fraction=_TEST_VALIDATION_FRACTION_SPLIT,
-            test_fraction=_TEST_TEST_FRACTION_SPLIT,
-        )
-
-        env = [
-            gca_env_var.EnvVar(name=str(key), value=str(value))
-            for key, value in _TEST_MODEL_SERVING_CONTAINER_ENVIRONMENT_VARIABLES.items()
-        ]
-
-        ports = [
-            gca_model.Port(container_port=port)
-            for port in _TEST_MODEL_SERVING_CONTAINER_PORTS
-        ]
-
-        true_container_spec = gca_model.ModelContainerSpec(
-            image_uri=_TEST_SERVING_CONTAINER_IMAGE,
-            predict_route=_TEST_SERVING_CONTAINER_PREDICTION_ROUTE,
-            health_route=_TEST_SERVING_CONTAINER_HEALTH_ROUTE,
-            command=_TEST_MODEL_SERVING_CONTAINER_COMMAND,
-            args=_TEST_MODEL_SERVING_CONTAINER_ARGS,
-            env=env,
-            ports=ports,
-        )
-
-        true_managed_model = gca_model.Model(
-            display_name=_TEST_DISPLAY_NAME + "-model",
-            description=_TEST_MODEL_DESCRIPTION,
-            container_spec=true_container_spec,
-            predict_schemata=gca_model.PredictSchemata(
-                instance_schema_uri=_TEST_MODEL_INSTANCE_SCHEMA_URI,
-                parameters_schema_uri=_TEST_MODEL_PARAMETERS_SCHEMA_URI,
-                prediction_schema_uri=_TEST_MODEL_PREDICTION_SCHEMA_URI,
-            ),
-            encryption_spec=_TEST_DEFAULT_ENCRYPTION_SPEC,
-        )
-
-        true_input_data_config = gca_training_pipeline.InputDataConfig(
-            fraction_split=true_fraction_split,
-            predefined_split=gca_training_pipeline.PredefinedSplit(
-                key=_TEST_PREDEFINED_SPLIT_COLUMN_NAME
-            ),
-            dataset_id=mock_tabular_dataset.name,
-            gcs_destination=gca_io.GcsDestination(
-                output_uri_prefix=_TEST_BASE_OUTPUT_DIR
-            ),
-        )
-
-        true_training_pipeline = gca_training_pipeline.TrainingPipeline(
-            display_name=_TEST_DISPLAY_NAME,
-            training_task_definition=schema.training_job.definition.custom_task,
-            training_task_inputs=json_format.ParseDict(
-                {
-                    "workerPoolSpecs": [true_worker_pool_spec],
-                    "baseOutputDirectory": {"output_uri_prefix": _TEST_BASE_OUTPUT_DIR},
-                },
-                struct_pb2.Value(),
-            ),
-            model_to_upload=true_managed_model,
-            input_data_config=true_input_data_config,
-            encryption_spec=_TEST_DEFAULT_ENCRYPTION_SPEC,
-        )
-
-        mock_pipeline_service_create.assert_called_once_with(
-            parent=initializer.global_config.common_location_path(),
-            training_pipeline=true_training_pipeline,
-        )
-
-        assert job._gca_resource is mock_pipeline_service_get.return_value
-
-        mock_model_service_get.assert_called_once_with(name=_TEST_MODEL_NAME)
-
-        assert model_from_job._gca_resource is mock_model_service_get.return_value
-
-        assert job.get_model()._gca_resource is mock_model_service_get.return_value
-
-        assert not job.has_failed
-
-        assert job.state == gca_pipeline_state.PipelineState.PIPELINE_STATE_SUCCEEDED
-
     @pytest.mark.parametrize("sync", [True, False])
     def test_run_call_pipeline_service_create_with_bigquery_destination(
         self,