Of course, PySyft has the ability to run in its own environment. But if you would like to train federated learning models in the browser, you must resort to using some ML framework like TensorFlow.js.
Syft.js is a microlibrary built on top of TensorFlow.js, allowing for a socket connection with any running PySyft instance.
PySyft acts as the parent node, instructing child nodes (Syft.js instances running in a website on users' browsers) of what tensors to add to a list, remove from a list, and operate against.
If you're using a package manage like NPM:
npm install --save syft.js
Or if Yarn is your cup of tea:
yarn add syft.js
When using a package manager, TensorFlow.js will be automatically installed.
If you're not using a package manager, you can also include Syft.js within a
<script src="https://cdnjs.cloudflare.com/ajax/libs/tensorflow/0.12.5/tf.min.js"></script><script src="https://unpkg.com/[email protected]/lib/index.js"></script>
For integration into your client-side application, please check out our guide.
For further API documentation, please check that out here.
Clone or fork
npm install or
npm start or
We're accepting PR's for testing at the moment to improve our overall code coverage. In terms of core functionality, we're considering the current version of Syft.js feature complete until a further roadmap is designated.