Requirements for using custom components with ML models

Package requirements

• The package type must be: source distribution (distributions of type Wheel and Egg are not supported)
• The package file format must be: .zip
• Any third-party dependencies for your custom components must be installable by pip and must be passed to the install_requires argument of the setup function of the setuptools library.

Refer to: Creating a source distribution

Storing your custom package

You must take extra steps when you store your trained model in the Watson Machine Learning repository:

• Store your custom package in the Watson Machine Learning repository (use the runtimes.store_library function from the watsonx.ai Python client, or the store libraries Watson Machine Learning CLI command.)
• Create a runtime resource object that references your stored custom package, and then store the runtime resource object in the Watson Machine Learning repository (use the runtimes.store function, or the store runtimes command.)
• When you store your trained model in the Watson Machine Learning repository, reference your stored runtime resource in the metadata that is passed to the store_model function (or the store command.)