flower-client
v1.0.2
Published
Node client for Flower Federated Learning (flower.dev)
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Flower NodeJs Client
Package that allows you to implement a Flower client in NodeJs in order to create federated learning with tensorflow.js.
Prerequisite
Install :
- python >= 3.6
- flower library :
pip install flwr
- nodejs
- npm
How to use
Same usage as the Python version. Create a client that override the client class and fill the 4 methods, like "example/tfjs_Client.js".
const {Client} = require('flower-client');
class Tfjs_Client extends Client{
...
}
Modify if necessary the "server.py" and run it. Finally, run the clients by using start_tfjs_client.
const {start_tfjs_client} = require('flower-client');
const tfjs_client = new Tfjs_Client();
await start_tfjs_client('<ip>:<port>', tfjs_Client,);
Run the example
- Clone repository
- Get into the folder :
cd <path to the folder>
- Installation:
npm i
- Get into the folder example:
cd example
- Run the server :
python server.py
- Run client#1 :
node index.js
- Run client#2 :
node index.js