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

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# mypy ignore arg types (for templated fields)
# type: ignore[arg-type]

"""
Example Airflow DAG for Google Vertex AI service testing Hyperparameter Tuning Job operations.
"""
from __future__ import annotations

import os
from datetime import datetime

from google.cloud import aiplatform

from airflow import models
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job import (
    CreateHyperparameterTuningJobOperator,
    DeleteHyperparameterTuningJobOperator,
    GetHyperparameterTuningJobOperator,
    ListHyperparameterTuningJobOperator,
)
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
[docs]DAG_ID = "vertex_ai_hyperparameter_tuning_job_operations"
[docs]REGION = "us-central1"
[docs]DISPLAY_NAME = f"hyperparameter-tuning-job-{ENV_ID}"
[docs]DATA_SAMPLE_GCS_BUCKET_NAME = f"bucket_hyperparameter_tuning_job_{ENV_ID}"
[docs]STAGING_BUCKET = f"gs://{DATA_SAMPLE_GCS_BUCKET_NAME}"
[docs]REPLICA_COUNT = 1
[docs]MACHINE_TYPE = "n1-standard-4"
[docs]ACCELERATOR_TYPE = "ACCELERATOR_TYPE_UNSPECIFIED"
[docs]ACCELERATOR_COUNT = 0
[docs]WORKER_POOL_SPECS = [ { "machine_spec": { "machine_type": MACHINE_TYPE, "accelerator_type": ACCELERATOR_TYPE, "accelerator_count": ACCELERATOR_COUNT, }, "replica_count": REPLICA_COUNT, "container_spec": { "image_uri": f"gcr.io/{PROJECT_ID}/horse-human:hypertune",
}, } ]
[docs]PARAM_SPECS = { "learning_rate": aiplatform.hyperparameter_tuning.DoubleParameterSpec(min=0.01, max=1, scale="log"), "momentum": aiplatform.hyperparameter_tuning.DoubleParameterSpec(min=0, max=1, scale="linear"), "num_neurons": aiplatform.hyperparameter_tuning.DiscreteParameterSpec( values=[64, 128, 512], scale="linear"
), }
[docs]METRIC_SPEC = { "accuracy": "maximize",
} with models.DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "vertex_ai", "hyperparameter_tuning_job"], ) as dag:
[docs] create_bucket = GCSCreateBucketOperator( task_id="create_bucket", bucket_name=DATA_SAMPLE_GCS_BUCKET_NAME, storage_class="REGIONAL", location=REGION,
) # [START how_to_cloud_vertex_ai_create_hyperparameter_tuning_job_operator] create_hyperparameter_tuning_job = CreateHyperparameterTuningJobOperator( task_id="create_hyperparameter_tuning_job", staging_bucket=STAGING_BUCKET, display_name=DISPLAY_NAME, worker_pool_specs=WORKER_POOL_SPECS, sync=False, region=REGION, project_id=PROJECT_ID, parameter_spec=PARAM_SPECS, metric_spec=METRIC_SPEC, max_trial_count=15, parallel_trial_count=3, ) # [END how_to_cloud_vertex_ai_create_hyperparameter_tuning_job_operator] # [START how_to_cloud_vertex_ai_get_hyperparameter_tuning_job_operator] get_hyperparameter_tuning_job = GetHyperparameterTuningJobOperator( task_id="get_hyperparameter_tuning_job", project_id=PROJECT_ID, region=REGION, hyperparameter_tuning_job_id=create_hyperparameter_tuning_job.output["hyperparameter_tuning_job_id"], ) # [END how_to_cloud_vertex_ai_get_hyperparameter_tuning_job_operator] # [START how_to_cloud_vertex_ai_delete_hyperparameter_tuning_job_operator] delete_hyperparameter_tuning_job = DeleteHyperparameterTuningJobOperator( task_id="delete_hyperparameter_tuning_job", project_id=PROJECT_ID, region=REGION, hyperparameter_tuning_job_id=create_hyperparameter_tuning_job.output["hyperparameter_tuning_job_id"], trigger_rule=TriggerRule.ALL_DONE, ) # [END how_to_cloud_vertex_ai_delete_hyperparameter_tuning_job_operator] # [START how_to_cloud_vertex_ai_list_hyperparameter_tuning_job_operator] list_hyperparameter_tuning_job = ListHyperparameterTuningJobOperator( task_id="list_hyperparameter_tuning_job", region=REGION, project_id=PROJECT_ID, ) # [END how_to_cloud_vertex_ai_list_hyperparameter_tuning_job_operator] delete_bucket = GCSDeleteBucketOperator( task_id="delete_bucket", bucket_name=DATA_SAMPLE_GCS_BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE, ) ( # TEST SETUP create_bucket # TEST BODY >> create_hyperparameter_tuning_job >> get_hyperparameter_tuning_job >> delete_hyperparameter_tuning_job >> list_hyperparameter_tuning_job # TEST TEARDOWN >> 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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