Update your code
- Update src/luna/train.py and add your training code
- Add your training code
- Save your model in models folder. You can save the model in a subdirectory, or a diffrent folder (not recommended)
- If your model is saved in a subdirectory of models folder or a different directory, update the model_path argument in the RegisterModel call
- Update the description argument in the RegisterModel call
- Update src/luna/batchinference.py and add your batch inference code
- Update the value of model_path variable if you want to download model to a different folder
- Add your inference code
- Delete the downloaded model after inference
- Update the run function in src/luna/score.py and add your scoring code
- Add anything you need to run when the container instance startes and every time when it restarts to the init() function
- Add your scoring code in the run() function and return the result. Use model_path global variable to locate your model (pre-downloaded to the container)
Update your environment
- Update the conda.yml to add your conda or pip dependencies
You are ready to go!