Antoine Poirier, Florent Pollet
Class project based on the study of this paper.
The report can be found here. The trained models for the report can be downloaded here.
- Make sure you have Python installed (version 3.8 or above).
- Navigate to this folder.
- Run
pip install -e .[cuda] -Uorpip install -e .[cpu] -U(tested on Windows and Mac).
To run the script about the class circle study, you can just run the file scripts/cc_circle.py with Python.
To run the study on embeddings, you can use the console script ccrun, like ccrun +dataset=house +loss=mse.
You can choose a dataset among house and synthetic. You can choose a loss between mse, supcon, nce, spread.
Please feel free to tune other parameters by overriding them (please see class_collapse/config and Hydra documentation).
The output will be in the folder outputs, automatically generated.
Please feel free to submit an issue if you have any questions.