Whats the issue?
Keeping track of all of the things you’ve tried and tested when training a machine learning model is tedious.
A secondary issue is that uploading files with sensitive data to Github is a bad idea, but if those files are needed for your project, what do you do?
How do you fix it?
With Paramerator! <- download link
- Load hyper-parameters (or any options really) from disk
- Save to disk
- Build a dictionary of ‘default files’ and their parameters
- Force user input for missing required parameters like IP addresses, passwords and API keys
- Works great in Jupyter Notebooks!
- Parameters become nested attributes so you can “tab-complete” all of them
- Type-aware. Store any standard python dtype
- Parameter files are human-readable and editable