Federated Learning Demonstrator MNIST Example

This repository contains an example client of a Federated Learning platform. The example shows how to create a client which trains a model based on the popular MNIST dataset. This repository also include many scripts to show how to interact with the Federated Learning platform directly.

The code of this MNIST example is based on the example from PyTorch.

This project is a component of the Federated Learning (FL) platform, serving as a proof of concept for the Catena-X project. The FL platform aims to demonstrate the potential of federated learning in a practical, real-world context.

For a comprehensive understanding of the FL platform, please refer to the official FL platform documentation.

A complete list of all repositories relevant to the FL platform can be found here.

Get Started

The code of this repository is part of the MNIST example client tutorial for the Federated Learning platform. The MNIST client implementation is based on the provided Federated Learning platform client base package.

This README.md is primarily intended for developers and contributors, providing necessary information for setup, installation, and contribution guidelines. If you're interested in using or testing this project, we recommend starting with the GitHub pages. They offer a more user-friendly interface and comprehensive guides to get you started.

Requirements

• python 3.10 or later
  which python
• virtualenv or venv
  pip install -U virtualenv
• jq command for JSON parsing inside bash
  sudo apt-get install jq

Install

```bash

create virtual environment

virtualenv -p $(which python3.10) .venv

or

python -m venv .venv

activate our virtual environment

source .venv/bin/activate

update pip (optional)

python -m pip install -U pip

install

./dev install -U -e ".[all]" ```

Helpers

```txt $ ./dev --help usage: ./dev [options]

positional arguments: {clean,coverage,coverage-report,doc,doc-build,docker-build,help,install,licenses,licenses-check,lint,lint-code,lint-doc,lint-scripts,mypy,safety-check,start,test,version,versions} Available sub commands help Show this help message and exit start Run the application docker-build Build docker images for local development test Run all tests lint Run all linter lint-code Run code linter lint-doc Run documentation linter lint-scripts Run bash script linter mypy Run type checker coverage Run unit tests coverage-report Generate test coverage report doc Start documentation server doc-build Build documentation licenses Generate licenses licenses-check Check licenses safety-check Check dependencies for known security vulnerabilities install Install package clean Clean up local files version Show package version versions Show versions

options: --no-http-serve Do not serve the action result via HTTP ```

Contribution

• Type-Save and linting with mypy+flake8
• Scripts and examples for linux, wsl (bash)

Documentation

This projects is using the Docstring style from Google. At least public classes, methods, fields, ... should be documented.

```python """ This is the single line short description.

This is the multiline or long description. Note, that the whole Docstring support markdown styling.

The long description can also contains multiple paragraphs.

Args: logfilepath (str): Log file path. ensurelog_dir (bool, optional): Create directory for the log file if not exists. Defaults to True.

Returns: Dict[str, Any]: logging configuration dict """ ```

Credits