Add Custom Recipes¶
Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime like plugins. Restarting Driverless AI is not required. If you do not have a custom recipe, you can select from a number of recipes available in the Recipes for H2O Driverless AI repository. For more information and examples, refer to Custom Recipe Management.
To add a custom recipe to Driverless AI, click Add Custom Recipe and select one of the following options:
From computer: Add a custom recipe as a Python or ZIP file from your local file system.
From URL: Add a custom recipe from a URL.
From Bitbucket: Add a custom recipe from a Bitbucket repository. To use this option, your Bitbucket username and password must be provided along with the custom recipe Bitbucket URL.
Official Recipes (Open Source)¶
To access H2O’s official recipes repository, click Official Recipes (Open Source).
Editing the TOML Configuration¶
To open the built-in TOML configuration editor, click TOML in the Expert Settings window.
If you change the default value of an expert setting from the Expert Settings window, that change is displayed in the TOML configuration editor. For example, if you set the Make MOJO scoring pipeline setting in the Experiment tab to Off, then the line
make_mojo_scoring_pipeline = "off" is displayed in the TOML editor.
The TOML configuration editor lets you manually add, remove, or edit expert setting parameters. To confirm your changes, click Save. The experiment preview updates to reflect your specified configuration changes. For a full list of available settings, see Expert Settings.
Do not edit the section below the
[recipe_activation] line. This section provides Driverless AI with information about which custom recipes can be used by the experiment. This is important for keeping experiments comparable when performing retrain / refit operations.
For information on TOML, see https://toml.io/en/v0.4.0.