Create a custom runtime image for Watson Machine Learning Accelerator
Use your own custom runtime image to run workloads.
- Create a custom Dockerfile using the built-in image as a base: For example:
From cp.icr.io/cp/cpd/wml-accelerator-runtime:v4.0.0-rt23.1-py3.10 RUN <your-customization-steps>
- Build and push the
image:
podman build -f Dockerfile -t <your-registry>/<your-image> .
- Push the image to your own
registry:
podman push <your-registry>/<your-image>
- For your OpenShift cluster to pull the image, update the global pull secret. For details, see: Updating the global cluster pull secret.
- Update the IBM Watson® Machine Learning
Accelerator CR to use the custom image:
- Edit the
wmla-install-info-cm
config map:$ oc describe cm wmla-install-info-cm -n wmla-03 ... Data ==== ... my_runtime_image: cp.icr.io/cp/cpd/wml-accelerator-runtime@sha256:9c3890214eeb00e2e80e6079576cc99ede1102729db1bd7a4a9c266434e60658
- Edit the Watson Machine Learning
Accelerator CR as
follows:
apiVersion: spectrumcomputing.ibm.com/v1 kind: Wmla spec: version: 4.0.0 ... selectedRuntimeImage: targetVersion: 4.0.0 imageRef: my_runtime_image
- Wait for the update to be applied. Verify that your runtime image is set. Restart the dlpd pod if needed.
- Edit the