tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package¶

用于测试 Google Vertex AI 服务自定义作业操作的示例 Airflow DAG。

函数¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.ENV_ID[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.PROJECT_ID[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.DAG_ID = 'vertex_ai_custom_job_operations'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.REGION = 'us-central1'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.PACKAGE_DISPLAY_NAME = 'train-housing-py-package-Uninferable'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.MODEL_DISPLAY_NAME = 'py-package-housing-model-Uninferable'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.RESOURCE_DATA_BUCKET = 'airflow-system-tests-resources'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.CUSTOM_PYTHON_GCS_BUCKET_NAME = ''[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.DATA_SAMPLE_GCS_OBJECT_NAME = 'vertex-ai/california_housing_train.csv'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.TABULAR_DATASET(bucket_name)[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.CONTAINER_URI = 'us-docker.pkg.dev/vertex-ai/training/tf-cpu.2-2:latest'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.MODEL_SERVING_CONTAINER_URI = 'us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-2:latest'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.REPLICA_COUNT = 1[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.MACHINE_TYPE = 'n1-standard-4'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.ACCELERATOR_TYPE = 'ACCELERATOR_TYPE_UNSPECIFIED'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.ACCELERATOR_COUNT = 0[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.TRAINING_FRACTION_SPLIT = 0.7[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.TEST_FRACTION_SPLIT = 0.15[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.VALIDATION_FRACTION_SPLIT = 0.15[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.PYTHON_PACKAGE_GCS_URI = 'gs:///vertex-ai/custom_trainer_script-0.1.tar'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.PYTHON_MODULE_NAME = 'aiplatform_custom_trainer_script.task'[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.create_bucket[源代码]¶

tests.system.google.cloud.vertex_ai.example_vertex_ai_custom_job_python_package.test_run[源代码]¶

`ENV_ID`
`PROJECT_ID`
`DAG_ID`
`REGION`
`PACKAGE_DISPLAY_NAME`
`MODEL_DISPLAY_NAME`
`RESOURCE_DATA_BUCKET`
`CUSTOM_PYTHON_GCS_BUCKET_NAME`
`DATA_SAMPLE_GCS_OBJECT_NAME`
`CONTAINER_URI`
`MODEL_SERVING_CONTAINER_URI`
`REPLICA_COUNT`
`MACHINE_TYPE`
`ACCELERATOR_TYPE`
`ACCELERATOR_COUNT`
`TRAINING_FRACTION_SPLIT`
`TEST_FRACTION_SPLIT`
`VALIDATION_FRACTION_SPLIT`
`PYTHON_PACKAGE_GCS_URI`
`PYTHON_MODULE_NAME`
`create_bucket`
`test_run`