Source code for airflow.providers.google.cloud.example_dags.example_automl_translation

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"""
Example Airflow DAG that uses Google AutoML services.
"""
import os
from datetime import datetime

from airflow import models
from airflow.providers.google.cloud.hooks.automl import CloudAutoMLHook
from airflow.providers.google.cloud.operators.automl import (
    AutoMLCreateDatasetOperator,
    AutoMLDeleteDatasetOperator,
    AutoMLDeleteModelOperator,
    AutoMLImportDataOperator,
    AutoMLTrainModelOperator,
)

[docs]GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "your-project-id")
[docs]GCP_AUTOML_LOCATION = os.environ.get("GCP_AUTOML_LOCATION", "us-central1")
[docs]GCP_AUTOML_TRANSLATION_BUCKET = os.environ.get( "GCP_AUTOML_TRANSLATION_BUCKET", "gs://INVALID BUCKET NAME/file"
) # Example values
[docs]DATASET_ID = "TRL123456789"
# Example model
[docs]MODEL = { "display_name": "auto_model_1", "dataset_id": DATASET_ID, "translation_model_metadata": {},
} # Example dataset
[docs]DATASET = { "display_name": "test_translation_dataset", "translation_dataset_metadata": { "source_language_code": "en", "target_language_code": "es",
}, }
[docs]IMPORT_INPUT_CONFIG = {"gcs_source": {"input_uris": [GCP_AUTOML_TRANSLATION_BUCKET]}}
[docs]extract_object_id = CloudAutoMLHook.extract_object_id
# Example DAG for AutoML Translation with models.DAG( "example_automl_translation", schedule_interval=None, # Override to match your needs start_date=datetime(2021, 1, 1), catchup=False, user_defined_macros={"extract_object_id": extract_object_id}, tags=['example'], ) as example_dag:
[docs] create_dataset_task = AutoMLCreateDatasetOperator( task_id="create_dataset_task", dataset=DATASET, location=GCP_AUTOML_LOCATION
) dataset_id = create_dataset_task.output["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 create_model = AutoMLTrainModelOperator(task_id="create_model", model=MODEL, location=GCP_AUTOML_LOCATION) model_id = create_model.output["model_id"] delete_model_task = AutoMLDeleteModelOperator( task_id="delete_model_task", model_id=model_id, location=GCP_AUTOML_LOCATION, project_id=GCP_PROJECT_ID, ) delete_datasets_task = AutoMLDeleteDatasetOperator( task_id="delete_datasets_task", dataset_id=dataset_id, location=GCP_AUTOML_LOCATION, project_id=GCP_PROJECT_ID, ) import_dataset_task >> create_model delete_model_task >> delete_datasets_task # Task dependencies created via `XComArgs`: # create_dataset_task >> import_dataset_task # create_dataset_task >> create_model # create_model >> delete_model_task # create_dataset_task >> delete_datasets_task

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