Creating user-defined libraries and runtimes

WML for z/OS provides extensive built-in machine learning frameworks to meet the need of the most common data transformation, model training, and model scoring tasks. If you import models that use additional transformers, estimators, or algorithms, you can create personalized libraries and runtimes required by those transformers and estimators.

In WML for z/OS, a user-defined library is a package that provides essential functions for training and scoring a model while a custom-built runtime consists of a set of libraries. A library package can be a jar or configuration file, such as a JSON configuration file.

1. Sign into the WML for z/OS web user interface with your user name and password.
2. From the sidebar, navigate to the Model Management page.
3. Create a new library.
   1. On the Model Management page, click the Runtimes tab.
   2. Click Add Library to launch the setting page for a new library.
   3. Specify attributes for the new library and select a library file for upload.
   4. Click Create to create the new library.
   5. If needed, repeat the procedure to create another new library.
4. Create a new runtime that consists of multiple custom-built libraries.
   1. On the Model Management page, click the Runtimes tab.
   2. Click New Runtime to launch the setting page for a new runtime.
   3. Specify attributes for the new runtime and select your own libraries to be included.
   4. Click Create to create the new runtime.
   5. If needed, repeat the procedure to create another new runtime.
5. Import a model that will use the new runtime.
6. Select a runtime to be associated with the imported model.
7. Train, deploy, and score the model.

   After you successfully deploy the imported model, you can treat and use the model as a normal WML for z/OS model. You can schedule it for online scoring, batch scoring, evaluation, and automatic retraining.