Source code for tests.system.providers.google.cloud.vertex_ai.example_vertex_ai_auto_ml_text_training

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"""
Example Airflow DAG for Google Vertex AI service testing Auto ML operations.
"""
from __future__ import annotations

import os
from datetime import datetime

from google.cloud.aiplatform import schema
from google.protobuf.struct_pb2 import Value

from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.gcs import (
    GCSCreateBucketOperator,
    GCSDeleteBucketOperator,
    GCSSynchronizeBucketsOperator,
)
from airflow.providers.google.cloud.operators.vertex_ai.auto_ml import (
    CreateAutoMLTextTrainingJobOperator,
    DeleteAutoMLTrainingJobOperator,
)
from airflow.providers.google.cloud.operators.vertex_ai.dataset import (
    CreateDatasetOperator,
    DeleteDatasetOperator,
    ImportDataOperator,
)
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
[docs]DAG_ID = "example_vertex_ai_auto_ml_operations"
[docs]REGION = "us-central1"
[docs]TEXT_DISPLAY_NAME = f"auto-ml-text-{ENV_ID}"
[docs]MODEL_DISPLAY_NAME = f"auto-ml-text-model-{ENV_ID}"
[docs]RESOURCE_DATA_BUCKET = "airflow-system-tests-resources"
[docs]TEXT_GCS_BUCKET_NAME = f"bucket_text_{DAG_ID}_{ENV_ID}".replace("_", "-")
[docs]TEXT_DATASET = { "display_name": f"text-dataset-{ENV_ID}", "metadata_schema_uri": schema.dataset.metadata.text, "metadata": Value(string_value="text-dataset"), }
[docs]TEXT_DATA_CONFIG = [ { "import_schema_uri": schema.dataset.ioformat.text.single_label_classification, "gcs_source": {"uris": [f"gs://{TEXT_GCS_BUCKET_NAME}/vertex-ai/text-dataset.csv"]}, }, ]
with DAG( f"{DAG_ID}_text_training_job", schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "vertex_ai", "auto_ml"], ) as dag:
[docs] create_bucket = GCSCreateBucketOperator( task_id="create_bucket", bucket_name=TEXT_GCS_BUCKET_NAME, storage_class="REGIONAL", location=REGION, )
move_dataset_file = GCSSynchronizeBucketsOperator( task_id="move_dataset_to_bucket", source_bucket=RESOURCE_DATA_BUCKET, source_object="vertex-ai/datasets", destination_bucket=TEXT_GCS_BUCKET_NAME, destination_object="vertex-ai", recursive=True, ) create_text_dataset = CreateDatasetOperator( task_id="text_dataset", dataset=TEXT_DATASET, region=REGION, project_id=PROJECT_ID, ) text_dataset_id = create_text_dataset.output["dataset_id"] import_text_dataset = ImportDataOperator( task_id="import_text_data", dataset_id=text_dataset_id, region=REGION, project_id=PROJECT_ID, import_configs=TEXT_DATA_CONFIG, ) # [START how_to_cloud_vertex_ai_create_auto_ml_text_training_job_operator] create_auto_ml_text_training_job = CreateAutoMLTextTrainingJobOperator( task_id="auto_ml_text_task", display_name=TEXT_DISPLAY_NAME, prediction_type="classification", multi_label=False, dataset_id=text_dataset_id, model_display_name=MODEL_DISPLAY_NAME, training_fraction_split=0.7, validation_fraction_split=0.2, test_fraction_split=0.1, sync=True, region=REGION, project_id=PROJECT_ID, ) # [END how_to_cloud_vertex_ai_create_auto_ml_text_training_job_operator] delete_auto_ml_text_training_job = DeleteAutoMLTrainingJobOperator( task_id="delete_auto_ml_text_training_job", training_pipeline_id="{{ task_instance.xcom_pull(task_ids='auto_ml_text_task', key='training_id') }}", region=REGION, project_id=PROJECT_ID, trigger_rule=TriggerRule.ALL_DONE, ) delete_text_dataset = DeleteDatasetOperator( task_id="delete_text_dataset", dataset_id=text_dataset_id, region=REGION, project_id=PROJECT_ID, trigger_rule=TriggerRule.ALL_DONE, ) delete_bucket = GCSDeleteBucketOperator( task_id="delete_bucket", bucket_name=TEXT_GCS_BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE, ) ( # TEST SETUP [ create_bucket >> move_dataset_file, create_text_dataset, ] >> import_text_dataset # TEST BODY >> create_auto_ml_text_training_job # TEST TEARDOWN >> delete_auto_ml_text_training_job >> delete_text_dataset >> delete_bucket ) from tests.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)

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