PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).

Related tags

Deep Learning scaffold pytorch federated-learning
Overview

Scaffold-Federated-Learning

PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).

Environment

numpy==1.18.5

pytorch==1.10.1+cu111

Experimental parameter settings

communication rounds: r=10,

number of local update steps: E=10,

=0.01,

=1,

total number of clients: K=10,

sampled num: |S|=5.

Usage

python server.py
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Comments
  • there maybe a mistake in client.py during updating local control variate

    there maybe a mistake in client.py during updating local control variate

    The local control variate update as follow in the origin papper. 截屏2022-05-03 下午5 01 57

    When using Option 2, K means the number of local update steps which equals to E*L/B, E is local epoch, L is the size of local dataset, B is local batch size 截屏2022-05-03 下午4 58 22 So I wonder if there is a mistake in client.py during updating local control variate at line 50 image

    opened by MrYYYYYYYYYYY 2
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KI
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