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El recurso TrainingPipeline de AutoML organiza las tareas asociadas con el entrenamiento de un modelo de AutoML. Este recurso siempre ejecuta la tarea de entrenamiento y, de forma opcional, puede exportar datos desde una Dataset de Vertex AI, que se convierte en la entrada de entrenamiento, sube el modelo a Vertex AI y lo evalúa. Para obtener información sobre el entrenamiento de AutoML en Vertex AI, consulta la documentación de entrenamiento de AutoML. Para obtener información sobre los Google Cloud componentes de canalización relacionados con los conjuntos de datos, consulta Componentes de conjuntos de datos.
El SDK Google Cloud incluye los siguientes operadores relacionados con los modelos y flujos de trabajo de AutoML:
Operadores relacionados con la previsión de AutoML
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-09-04 (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)."]]