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Currently the model pipeline on open shift uses GPU and has to be turned on and off manually. It would be better to have a process which triggers a mechanism to get the pod when needed. Here is a possible solution to the current process we aligned on today:
- Change Dockerfile (install kubectl)
corporate_data_extraction/data_extractor/code/coordinator/Dockerfile
RUN apt-get install -y kubectl
cp ... (maybe manifest to be added)
- Job on Open Shift (contains manifest)
-- has to be set-up to create the model-docker (model-pipeline-server-docker)
corporate_data_extraction/data_extractor/code/model_pipeline/Dockerfile
- entry.sh
change sleep infinity --> return exit code something
- Change code infer_on_pdf.py
corporate_data_extraction/data_extractor/code/infer_on_pdf.py Line 172: Something like that (maybe with Python package)
cmd = 'kubectl ...'
try:
os.system(cmd)
except Exception as e:
msg = "Error during kubectl"
return Response(msg, status=500)
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