Profila le prestazioni dell'addestramento del modello utilizzando Cloud Profiler nell'addestramento personalizzato con un container predefinito: notebook
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In questo tutorial imparerai ad attivare Profiler in Vertex AI per i job di addestramento personalizzato con un container predefinito.
Blocco note: Profila le prestazioni di addestramento del modello utilizzando Cloud Profiler nel container predefinito
Questo tutorial utilizza i seguenti servizi e risorse di Google Cloud ML:
Vertex AI Training
Vertex AI TensorBoard
I passaggi eseguiti includono:
Prepara il codice di addestramento personalizzato e caricalo come pacchetto Python in un container predefinito.
Crea ed esegui un job di addestramento personalizzato che attiva Profiler.
Visualizza la dashboard di Profiler per eseguire il debug delle prestazioni di addestramento del modello.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema รจ stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-02 UTC."],[],[],null,["# Profile model training performance using Cloud Profiler in custom training with prebuilt container: Notebook\n\nIn this tutorial, you learn how to enable Profiler in Vertex AI for\ncustom training jobs with a prebuilt container.\n\nNotebook: Profile model training performance using Cloud Profiler in prebuilt container\n---------------------------------------------------------------------------------------\n\n| To see an example of profile model training performance,\n| run the \"Profile model training performance using Cloud Profiler in custom training with prebuilt 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_profiler_custom_training_with_prebuilt_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_profiler_custom_training_with_prebuilt_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_profiler_custom_training_with_prebuilt_container.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/tensorboard/tensorboard_profiler_custom_training_with_prebuilt_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- Prepare your custom training code and load your training code as a Python package to a prebuilt container.\n- Create and run a custom training job that enables Profiler.\n- View the Profiler dashboard to debug your model training performance.\n\nRelevant content\n----------------\n\n- [Profile model training performance using Profiler](/vertex-ai/docs/training/tensorboard-profiler)"]]
