Configuring the ONNX compiler service for your ML for IBM z/OS
If you plan to import, deploy, and manage your ONNX models with ML for IBM z/OS®, you must first configure the required ONNX compiler service. With the service, your ONNX models are compiled into an executable format during import, uploaded into the MLz repository, and readied for deployment and scoring.
Before you begin
Only one ONNX compiler service is required for each installation of the MLz. Before you start, make sure that you have completed the following tasks:
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Make sure that the MLz core service that will be used to import the ONNX model must be installed and configured on hardware that is equivalent to or higher than the hardware where the MLz scoring will be deployed.
The core service performs ONNX model compilation using the z Deep Learning Compiler (zDLC) and generates model versions compatible only up to the hardware level on which it is installed. For example:- If you plan to use the IBM® z17™ on-chip AI accelerator for scoring ONNX models, both the core service and the scoring service must be configured on an IBM z17™.
- If you plan to use the IBM z16™ on-chip AI accelerator for scoring ONNX models, you can install the core service on either an IBM z16 or an IBM z17™, and the scoring service must run on IBM z16.
- Review the Installation roadmap and complete all preceding tasks in the sequence.
- Provision a z/OS Container Extensions (zCX) instance or a Linux® on Z server with Docker installed as required in Installing prerequisite hardware and software for ML for IBM z/OS.
- Make sure xlc utility is configured for <mlz_setup_userid> as described in Configuring user ID for setting up Machine Learning for IBM z/OS Enterprise.
- Create user <docker_user> with all required privileges as described in Additional configuration steps for ML for z/OS Enterprise.