flwr-monitoring

Name	flwr-monitoring JSON
Version	0.2.0 JSON
	download
home_page	https://github.com/kandola-network/KanFL
Summary	A package for monitoring Flower federated learning framework using Prometheus and WandB
upload_time	2024-09-03 03:27:38
maintainer	None
docs_url	None
author	Kandola
requires_python	>=3.7
license	MIT
keywords	flower monitoring federated learning prometheus wandb
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # Federated Learning Monitoring Library

## Overview

The Federated Learning Monitoring Library is designed to provide comprehensive monitoring capabilities for federated learning processes. This library extends existing federated learning strategies (like FedAvg) with monitoring tools such as Prometheus. It allows users to track various metrics related to training, communication, and resource usage, providing deep insights into the performance and efficiency of federated learning systems.

## Features

- **Custom Monitoring Strategy**: Wraps existing federated learning strategies with monitoring capabilities.
- **Prometheus Integration**: Supports Prometheus as a monitoring tool out-of-the-box.
- **Resource Usage Tracking**: Monitors CPU, memory, and GPU usage.
- **Comprehensive Metrics**: Tracks training time, communication time, client participation, accuracy, loss, and more.

## Installation

To install the library, clone the repository and install the dependencies using pip:

```bash
git clone git@github.com:kandola-network/KanFL.git
cd KanFL
pip install -r requirements.txt


            

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