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Die AutoML-Ressource TrainingPipeline orchestriert die Aufgaben für das Training eines AutoML-Modells. Diese Ressource führt immer die Trainingsaufgabe aus und exportiert optional auch Daten aus einem Vertex AI-Dataset, das zur Trainingseingabe verwendet wird, lädt das Modell in Vertex AI hoch und bewertet das Modell. Informationen zum AutoML-Training in Vertex AI finden Sie in der Dokumentation zum AutoML-Training. Informationen zu Google Cloud Pipeline-Komponenten mit Bezug auf Datasets finden Sie unter Dataset-Komponenten.
Das Google Cloud SDK enthält die folgenden Operatoren mit Bezug auf AutoML-Modelle und -Workflows:
[[["Leicht verständlich","easyToUnderstand","thumb-up"],["Mein Problem wurde gelöst","solvedMyProblem","thumb-up"],["Sonstiges","otherUp","thumb-up"]],[["Schwer verständlich","hardToUnderstand","thumb-down"],["Informationen oder Beispielcode falsch","incorrectInformationOrSampleCode","thumb-down"],["Benötigte Informationen/Beispiele nicht gefunden","missingTheInformationSamplesINeed","thumb-down"],["Problem mit der Übersetzung","translationIssue","thumb-down"],["Sonstiges","otherDown","thumb-down"]],["Zuletzt aktualisiert: 2025-08-19 (UTC)."],[],[],null,["# Vertex AI AutoML components\n\nThe AutoML `TrainingPipeline` resource orchestrates tasks associated\nwith training an AutoML model. This resource always executes the\ntraining task, and optionally may also export data from a Vertex AI\n`Dataset` which becomes the training input, upload the Model to\nVertex AI, and evaluate the Model. For information about\nAutoML training in Vertex AI, see the\n[AutoML training documentation](/vertex-ai/docs/training-overview#automl). For information\nabout Google Cloud Pipeline Components related to datasets, see\n[Dataset components](/vertex-ai/docs/pipelines/dataset-component).\n\nThe Google Cloud SDK includes the following operators related to\nAutoML models and workflows:\n\n**Operators related to AutoML forecasting**\n\n\n- [`ProphetTrainerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/forecasting.html#v1.automl.forecasting.ProphetTrainerOp)\n\n\u003cbr /\u003e\n\n**Operators related to AutoML Tabular models**\n\n\n- [`CvTrainerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.CvTrainerOp)\n- [`EnsembleOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.EnsembleOp)\n- [`FinalizerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.FinalizerOp)\n- [`InfraValidatorOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.InfraValidatorOp)\n- [`SplitMaterializedDataOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.SplitMaterializedDataOp)\n- [`Stage1TunerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.Stage1TunerOp)\n- [`StatsAndExampleGenOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.StatsAndExampleGenOp)\n- [`TrainingConfiguratorAndValidatorOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.TrainingConfiguratorAndValidatorOp)\n- [`TransformOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.TransformOp)\n\n\u003cbr /\u003e\n\n**Operators related to AutoML `model` resource creation**\n\n\n- [`AutoMLForecastingTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLForecastingTrainingJobRunOp)\n- [`AutoMLImageTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLImageTrainingJobRunOp)\n- [`AutoMLTabularTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLTabularTrainingJobRunOp)\n- [`AutoMLTextTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLTextTrainingJobRunOp)\n- [`AutoMLVideoTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_jobAutoMLVideoTrainingJobRunOp)\n\n\u003cbr /\u003e\n\n[Learn more about training and using your own AutoML models](/vertex-ai/docs/training-overview#automl).\n\nAPI reference\n-------------\n\n- For AutoML component reference, see the\n [Google Cloud SDK reference for AutoML components](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html).\n\n- For Vertex AI API reference, see the following API reference pages:\n\n - [`Dataset` resource](/vertex-ai/docs/reference/rest/v1/projects.locations.datasets)\n\n - [`TrainingPipeline` resource](/vertex-ai/docs/reference/rest/v1/projects.locations.trainingPipelines)\n\nTutorials\n---------\n\n- [Learn how to use the Google Cloud pipeline components to train an image classification model using Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_automl_images.ipynb)\n- [Learn how to use the Google Cloud pipeline components to train a classification model using tabular data and Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/automl_tabular_classification_beans.ipynb)\n- [Learn how to use the Google Cloud pipeline components to train a linear regression model using tabular data and Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_automl_tabular.ipynb)\n- [Learn how to use the Google Cloud pipeline components to train a text classification model using Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_automl_text.ipynb)\n- [Learn how to use the Google Cloud pipeline components to upload and deploy a model.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_model_train_upload_deploy.ipynb)\n\nVersion history and release notes\n---------------------------------\n\nTo learn more about the version history and changes to the Google Cloud Pipeline Components SDK, see the [Google Cloud Pipeline Components SDK Release Notes](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/release.html).\n\n### Technical support contacts\n\nIf you have any questions, reach out to\n[kubeflow-pipelines-components@google.com](mailto: kubeflow-pipelines-components@google.com)."]]
