This project is created for Udacity's Secure and Private AI challenge course. It explores possibility to have PySyft worker running in the web browser, which potentially expands PySyft functionality to a very large user-base. The back-end for tensor operations in browser is tf.js.
The current project's state is 'proof of concept' where tensors can be moved to/from browser and a limited set of tensor operations is possible. Further direction is to try to use web client for federated learning.
Follow this Colab jupyter notebook.
For local installation:
pip install -Ur requirements.txt
python run_socketio_server.py
Update index.html and notebook code with server's URL (e.g. http://localhost:5000).
There's zero infrastructure work done (e.g. dependency management, building, etc.), and javascript is tested in Chrome only.
- syft.js - inspiration :)
- PySyft Android Worker - server script and some PySyft protocol details
- Numpy to array code borrowed from: https://gist.github.com/nvictus/88b3b5bfe587d32ac1ab519fd0009607
- Array to numpy code borrowed from: https://github.com/propelml/tfjs-npy/blob/master/npy.ts
- Thanks Udacity's Secure and Private AI challenge course and Andrew Trask for great content