This repository contains jupyter notebooks for developing self-supervised learning models for spectrum data processing.
Setup
The notebooks and python files should be in a same folder. Model constants and paths which are in separate file SSLConstants.py should be adapted to the user working environment (models saving paths, loading paths, ect.)
Experimenting
Dataset for training models and example model with corresonding statistics file are provided in the shared/self-supervised-learning folder on the server. Training models and saving statictics data is performed with the TrainScript.ipynb python notebook. Check the comments in the notebook for more details. Python notebook for model analysis, evaluation and visualization is provided as ModelAnalysis.ipynb. All the necessary functions for both notebooks are contained in the SSLUtils.py file. In the current state, when working all the files should be in a same folder.
The project is in active development, so optimizations are lacking and feedback is welcomed.