Flower Simulation Step-by-Step

This directory contains the code developed in the Flower Simulation tutorial series on Youtube. You can find all the videos here or clicking on the video preview below.

• In Part-I (7 videos) we developed from scratch a complete Federated Learning pipeline for simulation using PyTorch.

• In Part-II (2 videos) we enhanced the code in Part-I by making a better use of Hydra configs.

Constructing your Python Environment

As presented in the video, we first need to create a Python environment. You are free to choose the tool you are most familiar with, we’ll be using conda in this tutorial. You can create the conda and setup the environment as follows:

# I'm assuming you are running this on an Ubuntu 22.04 machine (GPU is not required)

# create the environment
conda create -n flower_tutorial python=3.8 -y

# activate your environment (depending on how you installed conda you might need to use `conda activate ...` instead)
source activate flower_tutorial

# install PyToch (other versions would likely work)
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.6 -c pytorch -c nvidia -y
# conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 -c pytorch # If you don't have a GPU

# install flower (for FL) and hydra (for configs)
pip install flwr==1.4.0 hydra-core==1.3.2
# install ray
# you might see some warning messages after installing it (you can ignore them)
pip install ray==1.11.1

If you are running this on macOS with Apple Silicon (i.e. M1, M2), you’ll need a different grpcio package if you see an error when running the code. To fix this do:

# with your conda environment activated
pip uninstall grpcio

conda install grpcio -y