def test_execute(self, mock_extract_object_id, mock_create_dataset,
                  mock_xcom):
     op = AutoMLCreateDatasetOperator(
         dataset=DATASET,
         location=GCP_LOCATION,
         project_id=GCP_PROJECT_ID,
         task_id=TASK_ID,
     )
     op.execute(context=None)
     mock_create_dataset.assert_called_once_with(
         dataset=DATASET,
         location=GCP_LOCATION,
         metadata=None,
         project_id=GCP_PROJECT_ID,
         retry=None,
         timeout=None,
     )
     mock_xcom.assert_called_once_with(None,
                                       key="dataset_id",
                                       value=DATASET_ID)
示例#2
0
IMPORT_INPUT_CONFIG = {"gcs_source": {"input_uris": [GCP_AUTOML_TEXT_BUCKET]}}

default_args = {"start_date": days_ago(1)}
extract_object_id = CloudAutoMLHook.extract_object_id

# Example DAG for AutoML Natural Language Entities Extraction
with models.DAG(
        "example_automl_text",
        default_args=default_args,
        schedule_interval=None,  # Override to match your needs
        user_defined_macros={"extract_object_id": extract_object_id},
        tags=['example'],
) as example_dag:
    create_dataset_task = AutoMLCreateDatasetOperator(
        task_id="create_dataset_task",
        dataset=DATASET,
        location=GCP_AUTOML_LOCATION)

    dataset_id = (
        '{{ task_instance.xcom_pull("create_dataset_task", key="dataset_id") }}'
    )

    import_dataset_task = AutoMLImportDataOperator(
        task_id="import_dataset_task",
        dataset_id=dataset_id,
        location=GCP_AUTOML_LOCATION,
        input_config=IMPORT_INPUT_CONFIG,
    )

    MODEL["dataset_id"] = dataset_id
示例#3
0
# Example DAG to create dataset, train model_id and deploy it.
with models.DAG(
    "example_create_and_deploy",
    default_args=default_args,
    schedule_interval=None,  # Override to match your needs
    user_defined_macros={
        "get_target_column_spec": get_target_column_spec,
        "target": TARGET,
        "extract_object_id": extract_object_id,
    },
) as create_deploy_dag:
    # [START howto_operator_automl_create_dataset]
    create_dataset_task = AutoMLCreateDatasetOperator(
        task_id="create_dataset_task",
        dataset=DATASET,
        location=GCP_AUTOML_LOCATION,
        project_id=GCP_PROJECT_ID,
    )

    dataset_id = (
        "{{ task_instance.xcom_pull('create_dataset_task', key='dataset_id') }}"
    )
    # [END howto_operator_automl_create_dataset]

    MODEL["dataset_id"] = dataset_id

    # [START howto_operator_automl_import_data]
    import_dataset_task = AutoMLImportDataOperator(
        task_id="import_dataset_task",
        dataset_id=dataset_id,
        location=GCP_AUTOML_LOCATION,