Closed adelton closed 8 months ago
But that is not possible with latest OpenShift AI -- either the user can select 2023.1, or the latest (and Recommended).
This part of the problem now reported as https://issues.redhat.com/browse/RHOAIENG-1054.
I now retried the tutorial with https://access.redhat.com/documentation/en-us/red_hat_openshift_ai_self-managed/2.7/html-single/openshift_ai_tutorial_-_fraud_detection_example/index#navigating-to-the-dashboard on OpenShift 4.15 and OpenShift AI 2.7 and the first cell content is
!pip install onnx onnxruntime seaborn tf2onnx
which passed.
Presumably this issue was fixed via https://github.com/rh-aiservices-bu/fraud-detection/pull/14.
When creating a workbench in OpenShift AI 2.5, the default and labelled Recommended version of the TensorFlow image is 2023.2.
However, with that image, running the first cell
in 1_experiment_train.ipynb yields
The step 4 in https://access.redhat.com/documentation/en-us/red_hat_openshift_ai_self-managed/2-latest/html-single/fraud_detection_tutorial/index#creating-a-workbench says "Select the latest Tensorflow image." and shows a selection of 2023.1 (Recommended).
But that is not possible with latest OpenShift AI -- either the user can select 2023.1, or the latest (and Recommended).
In any case, the notebook should work with the latest product version (and latest images) without errors.