Registering a model using Jupyter

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From the toolbar, click on the “Register a new model with ModelOp Center” icon.

1. The “Add Model to Model Operations Center” window opens. Click in the left side of the code cells to designate that the code is part of the model. The selected cells will have a highlighted green border on the left.

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2. Click Next. In the “Model Information” section, type the Model Name. Optionally, you can add a brief Description of the model.
   
   

    

3. Click Next. In the “Cell details” section:

   1. Choose the remote repository configuration. Make sure ModelOp Center has been configured with access to the git repositories.
      If the Git Remote text field is blank it will create a local (to ModelOp Center) git repository (no remote repository associated).
      If the Git Remote text field is provided (with a valid accessible git repository URL), the local copy will be associated with given remote repository.
      Check Use default repo option if you want the same git remote and branch for all the source code assets (cells). Otherwise, specify each asset with a different remote url or branch.
      You can entirely disable git handling by switching off the Remote repo configuration toggle. This will in turn handle the source code assets using ModelOp Center internal storage only.

   2. Provide a File Name, and select Primary Model Source if appropriate.
      The file name will be complemented with a default extension, but it can be provided by the input text field as part of the file name.
      A model must have one and only one primary source code, which is where it will look for the model functions (more on model functions in the next step).

       

4. Click Next. Specify the model functions used in your code. (For additional information on the model functions please see here.) ModelOp Center allows the user to associate the triggering operations with specific code functions. Additionally it can identify if the functions already have predefined model functions associated via smart tags. These optional smart tags should be presented as comments in the line above the function definition and the supported comments are:

   • modelop.init

   • modelop.score

   • modelop.metrics

   • modelop.training

   
   For example:

   # modelop.init def begin(): ...

   
   You will find that the functions identified from source with a smart tag are already associated with one of the functions, and this selection is not modifiable. If you wish to change the associated model function, either you can edit or remove the smart tag comment, or you can modify the associated model function in the ModelOp Center UI.
   
   The function associated via smart tag cannot be used for multiple model functions, but the remaining functions can be selected as options for the other associations:

    

5. Click Next. On the next screen, add any attachments associated the model and select an asset role for each of the files to upload. This will help ModelOp Center runtime identify the accompanying assets for different purposes across the Model Life Cycle. Leave the asset role blank to let ModelOp Center automatically identify the asset based on the file type.
   
   

    

6. Click Next. Review the summary and click Submit Model.