Profile model training performance using Cloud Profiler in custom training with prebuilt container: Notebook Stay organized with collections Save and categorize content based on your preferences.
In this tutorial, you learn how to enable Profiler in Vertex AI for custom training jobs with a prebuilt container.
Notebook: Profile model training performance using Cloud Profiler in prebuilt container
This tutorial uses the following Google Cloud ML services and resources:
Vertex AI training
Vertex AI TensorBoard
The steps performed include:
Prepare your custom training code and load your training code as a Python package to a prebuilt container.
Create and run a custom training job that enables Profiler.
View the Profiler dashboard to debug your model training performance.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-10-29 UTC."],[],[]]