Entrenamiento personalizado de Vertex AI TensorBoard con contenedor personalizado: Notebook
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En este instructivo, aprenderás a crear un trabajo de entrenamiento personalizado con contenedores personalizados y a supervisar tu proceso de entrenamiento en Vertex AI TensorBoard casi en tiempo real.
Notebook: Crea trabajos de entrenamiento personalizados con contenedores personalizados
En este instructivo, se usan los siguientes Google Cloud servicios y recursos de AA:
Vertex AI Training
Vertex AI TensorBoard
Los pasos realizados incluyen los siguientes:
Crea un repositorio y una configuración de Docker.
Crea una imagen de contenedor personalizada con el código de entrenamiento personalizado.
Configura una cuenta de servicio y buckets de Cloud Storage.
Crea e inicia el trabajo de entrenamiento personalizado con tu contenedor personalizado.
[[["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 TensorBoard custom training with custom container: Notebook\n\nIn this tutorial, you learn how to create a custom training job using custom\ncontainers, and monitor your training process on Vertex AI TensorBoard\nin near real time.\n\nNotebook: Create custom training jobs using custom containers\n-------------------------------------------------------------\n\n| To see an example of tensorboard custom training with custom container,\n| run the \"Vertex AI TensorBoard custom training with custom container\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Ftensorboard%2Ftensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Ftensorboard%2Ftensorboard_custom_training_with_custom_container.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_custom_training_with_custom_container.ipynb)\n\nThis tutorial uses the following Google Cloud ML services and resources:\n\n- Vertex AI training\n- Vertex AI TensorBoard\n\nThe steps performed include:\n\n- Create a Docker repository and config.\n- Create a custom container image with your customized training code.\n- Set up a service account and Cloud Storage buckets.\n- Create and launch your custom training job with your custom container.\n\nRelevant content\n----------------\n\n- [Vertex AI TensorBoard](/vertex-ai/docs/experiments/tensorboard-introduction)\n- [Custom training](/vertex-ai/docs/training/overview)"]]
