I had configured my local environment successfully to work with the Keras extensions. Specifically I was using a Keras Network Learner Node w/o any problems… except for performance on my small machine.
So I went ahead and configured a KNIME server (mount point) offered by my IT department, copied my workflow over to that server and tried it out. I got the following error:
ERROR Keras Network Learner 2:127 Execute failed: Selected Keras back end ‘Keras (TensorFlow)’ is not available anymore. Please check your local installation.
Details: Installation test for Python back end ‘org.knime.dl.keras.tensorflow.core.DLKerasTensorFlowNetwork’ timed out. Please make sure your Python environment is properly set up and consider increasing the timeout (currently 25000 ms) using the VM option ‘-Dknime.dl.installationtesttimeout=<value-in-ms>’.
I figured maybe Python was not configured on the server properly so I went back to the local copy of the workflow… and got the same error message?!
Finding this strange I disconnected from the server and restarted KNIME but still got the error using the local workflow.
So I finally completely removed the server / mount point from my configuration again and now the local workflow runs again.
So for some odd reason having an additional server configured makes the Keras integration somehow fail even when that server is not used and not even connected. Browsing the known issues I couldn’t find anything which seems to be related.
So if anyone has an idea what’s going on that would be highly appreciated!