pipelines-hyperdrive-step

Exercise Instructions

Open hyperdrive_pipeline.ipynb and follow the instructions in the notebook.

Running this via CLI

You can also run the Hyperdrive Hyperparameter Tuning via CLI:

az ml folder attach -w <YOUR WORKSPACE NAME> -g <YOUR RESOURCE GROUP>
az ml run submit-hyperdrive --hyperdrive-configuration-name hyperdrive_config.yml -c hyperdrive -e hyperdrive-test

In this case:

• hyperdrive_config.yml holds the configuration for the hyperparameter tuning. Full details on the parameters can be found here
• hyperdrive.runconfig holds the general script definition (which dataset, cluster, etc.)
• train.py takes all the hyperparameters as argument inputs

You can check the results in the Studio UI (navigate to the run, then select Child Runs):

Each Hyperparameter permutation will be executed in its own child run.

Knowledge Check

To be written