https://github.com/kitsuyaazuma/dsflplus

The implementation of DS-FL+ (Energy-based Knowledge Distillation for Communication-Efficient Federated Learning, IEICE 2024 student poster session).
https://github.com/kitsuyaazuma/dsflplus

federated-learning fedlab knowledge-distillation ood-detection pytorch

Last synced: 4 months ago
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The implementation of DS-FL+ (Energy-based Knowledge Distillation for Communication-Efficient Federated Learning, IEICE 2024 student poster session).

• Host: GitHub
• URL: https://github.com/kitsuyaazuma/dsflplus
• Owner: kitsuyaazuma
• Created: 2024-01-12T05:42:19.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-12-14T01:32:04.000Z (over 1 year ago)
• Last Synced: 2026-01-20T06:44:32.210Z (4 months ago)
• Topics: federated-learning, fedlab, knowledge-distillation, ood-detection, pytorch
• Language: Python
• Homepage: https://kitsuyaazuma.github.io/DSFLplus/
• Size: 5.42 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
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# DS-FL+

> [!NOTE]

> The implementation of **DS-FL+** (Energy-based Knowledge Distillation for Communication-Efficient Federated Learning, IEICE 2024 student poster session) is available [here](https://github.com/Kitsuya0828/DSFLplus/tree/v1.0.0).

This is the implementation of **DS-FL+** (Energy-based Thresholding and Knowledge Distillation for Communication-Efficient Federated Learning on Non-IID Data).

## Requirements

* Python version: `3.10.13`

* CUDA version: `11.6`

## Setup

```bash

git clone https://github.com/Kitsuya0828/DSFLplus.git

cd DSFLplus

conda env create -f env.yaml

conda activate dsflplus

# or

# https://pytorch.org/get-started/previous-versions/

conda create -n dsflplus python=3.10.13

conda activate dsflplus

pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116

pip install black fedlab gdown isort matplotlib mypy pandas plotly tensorboard

```

## Run

```bash

cd src

python main.py --help

# or

python main.py \

--algorithm=dsflplus \

--task=cifar10 \

--partition=shards \

--num_shards_per_client=2 \

--seed=42 \

--public_private_split=even_class \

--private_size=40000 \

--public_size=10000 \

--public_size_per_round=1000 \

--sample_ratio=1.0 \

--com_round=1000 \

--temperature=0.1 \

--total_clients=100 \

--batch_size=100 \

--epochs=5 \

--lr=0.1 \

--kd_epochs=5 \

--kd_batch_size=100 \

--kd_lr=0.1 \

--ood_detection_score=energy \

--ood_detection_threshold_delta=0.0025 \

--test_batch_size=500 \

--comment=shards_energy_delta00025

```