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It looks to me like these two steps of the pipeline train a bunch of models, saves them to outputs/ridge_{alpha}.pkl in train-sklearn.py, and then registers an entirely different .pkl file that was already checked in under model-deployment/sklearn_regression_model.pkl. Shouldn't it be registering one of the models it created?
`- task: AzureCLI@1
inputs:
azureSubscription: 'build-demo'
scriptLocation: 'inlineScript'
inlineScript: 'az ml run submit-script -c sklearn -e test -d training-env.yml train-sklearn.py'
workingDirectory: 'model-training'
- task: AzureCLI@1
inputs:
azureSubscription: 'build-demo'
scriptLocation: 'inlineScript'
inlineScript: 'az ml model register -n mymodel -p sklearn_regression_model.pkl -t model.json'
workingDirectory: 'model-deployment'`
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