Packaging a model to submit it to Vertex AI as a training job

The previous section demonstrated a small image colorization experiment on a Vertex AI Workbench notebook. Notebooks are great for small-scale and quick experiments, but when it comes to large-scale experiments (with more compute and/or memory requirements), it is advised to launch them as a Vertex AI job and specify desired machine specifications (accelerators such as GPU or TPU if needed) for optimal experimentation. Vertex AI jobs also let us execute tons of experiments in parallel without waiting for the results of a single experiment. Experiment tracking is also quite easy with Vertex AI jobs, so it becomes easier to compare your latest experiments with past experiments with the help of saved metadata and the Vertex AI UI. Now, let’s use our model experimentation setup from the previous section and launch it as a Vertex AI training job.

Important note

Vertex AI jobs run in a containerized environment,...