diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index 182cea1194fe..e694e39c6df5 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -18,6 +18,9 @@ README.md @jafermarq @tanertopal @danieljanes # Flower Examples /examples @yan-gao-GY @panh99 @chongshenng @jafermarq @tanertopal @danieljanes +# Flower Hub +/hub @yan-gao-GY @panh99 @chongshenng @jafermarq @tanertopal @danieljanes + # Flower Intelligence /intelligence/dev @charlesbvll @tanertopal @danieljanes /intelligence/docs @charlesbvll @tanertopal @danieljanes diff --git a/.github/workflows/framework-e2e.yml b/.github/workflows/framework-e2e.yml index f283bb155b41..c98b3dfd407a 100644 --- a/.github/workflows/framework-e2e.yml +++ b/.github/workflows/framework-e2e.yml @@ -342,7 +342,7 @@ jobs: python -m pip install "flwr[simulation] @ ${WHEEL_URL}" - name: Install project dependencies if: ${{ needs.changes.outputs.framework == 'true' }} - working-directory: examples/${{ matrix.example }} + working-directory: hub/apps/${{ matrix.example }} run: | sed -i 's/"flwr\[[^]]*\][^"]*", *//g' pyproject.toml # Replace tensorflow with tensorflow-cpu to avoid GPU warnings in CI @@ -351,7 +351,7 @@ jobs: pip install . --extra-index-url https://download.pytorch.org/whl/cpu - name: Run project if: ${{ needs.changes.outputs.framework == 'true' }} - working-directory: examples/${{ matrix.example }} + working-directory: hub/apps/${{ matrix.example }} run: | flwr run --run-config num-server-rounds=1 --stream 2>&1 | tee flwr_output.log output=$(flwr ls --format=json) diff --git a/.github/workflows/framework-test.yml b/.github/workflows/framework-test.yml index 1a82dd164633..c57cf80150a7 100644 --- a/.github/workflows/framework-test.yml +++ b/.github/workflows/framework-test.yml @@ -38,7 +38,7 @@ jobs: - 'dev/uv.lock' - '.github/workflows/framework-test.yml' ex_bench: - - 'examples/**/*' + - 'hub/apps/**/*' - 'benchmarks/**/*' - 'dev/test.sh' - '.github/workflows/framework-test.yml' diff --git a/.gitignore b/.gitignore index 6a545110e61b..a6783fa4795a 100644 --- a/.gitignore +++ b/.gitignore @@ -10,9 +10,9 @@ flwr_logs # Node.js node_modules -# Flower Examples -examples/**/dataset/** -#examples/**/dev/*.sh +# Flower Apps +hub/apps/**/dataset/** +#hub/apps/**/dev/*.sh # Flower Baselines baselines/datasets/leaf diff --git a/README.md b/README.md index 99e91e12e182..20f0048392f6 100644 --- a/README.md +++ b/README.md @@ -111,34 +111,33 @@ Several code examples show different usage scenarios of Flower (in combination w Quickstart examples: -- [Quickstart (TensorFlow)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-tensorflow) -- [Quickstart (PyTorch)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-pytorch) -- [Quickstart (Hugging Face)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-huggingface) -- [Quickstart (PyTorch Lightning)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-pytorch-lightning) -- [Quickstart (fastai)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-fastai) -- [Quickstart (Pandas)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-pandas) -- [Quickstart (JAX)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-jax) -- [Quickstart (MONAI)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-monai) -- [Quickstart (scikit-learn)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-sklearn) -- [Quickstart (Android [TFLite])](https://github.com/flwrlabs/flower/tree/main/examples/android) -- [Quickstart (iOS [CoreML])](https://github.com/flwrlabs/flower/tree/main/examples/ios) -- [Quickstart (MLX)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-mlx) -- [Quickstart (XGBoost)](https://github.com/flwrlabs/flower/tree/main/examples/xgboost-quickstart) -- [Quickstart (CatBoost)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-catboost) - -Other [examples](https://github.com/flwrlabs/flower/tree/main/examples): - -- [Raspberry Pi & Nvidia Jetson Tutorial](https://github.com/flwrlabs/flower/tree/main/examples/embedded-devices) -- [PyTorch: From Centralized to Federated](https://github.com/flwrlabs/flower/tree/main/examples/pytorch-from-centralized-to-federated) -- [Vertical FL](https://github.com/flwrlabs/flower/tree/main/examples/vertical-fl) -- [Federated Finetuning of OpenAI's Whisper](https://github.com/flwrlabs/flower/tree/main/examples/whisper-federated-finetuning) -- [Federated Finetuning of Large Language Model](https://github.com/flwrlabs/flower/tree/main/examples/flowertune-llm) -- [Federated Finetuning of a Vision Transformer](https://github.com/flwrlabs/flower/tree/main/examples/flowertune-vit) -- [Advanced Flower with PyTorch](https://github.com/flwrlabs/flower/tree/main/examples/advanced-pytorch) -- [Comprehensive Flower+XGBoost](https://github.com/flwrlabs/flower/tree/main/examples/xgboost-comprehensive) -- [Flower with KaplanMeierFitter from the lifelines library](https://github.com/flwrlabs/flower/tree/main/examples/federated-kaplan-meier-fitter) -- [Sample Level Privacy with Opacus](https://github.com/flwrlabs/flower/tree/main/examples/opacus) -- [Flower with a Tabular Dataset](https://github.com/flwrlabs/flower/tree/main/examples/fl-tabular) +- [Quickstart (TensorFlow)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-tensorflow) +- [Quickstart (PyTorch)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-pytorch) +- [Quickstart (Hugging Face)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-huggingface) +- [Quickstart (PyTorch Lightning)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-pytorch-lightning) +- [Quickstart (fastai)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-fastai) +- [Quickstart (Pandas)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-pandas) +- [Quickstart (JAX)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-jax) +- [Quickstart (MONAI)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-monai) +- [Quickstart (scikit-learn)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-sklearn) +- [Quickstart (Android [TFLite])](https://github.com/flwrlabs/flower/tree/main/hub/apps/android) +- [Quickstart (iOS [CoreML])](https://github.com/flwrlabs/flower/tree/main/hub/apps/ios) +- [Quickstart (MLX)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-mlx) +- [Quickstart (XGBoost)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-xgboost) +- [Quickstart (CatBoost)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-catboost) + +Other [examples](https://github.com/flwrlabs/flower/tree/main/hub/apps): + +- [Raspberry Pi & Nvidia Jetson Tutorial](https://github.com/flwrlabs/flower/tree/main/hub/apps/embedded-devices) +- [Vertical FL](https://github.com/flwrlabs/flower/tree/main/hub/apps/vertical-fl) +- [Federated Finetuning of OpenAI's Whisper](https://github.com/flwrlabs/flower/tree/main/hub/apps/whisper-federated-finetuning) +- [Federated Finetuning of Large Language Model](https://github.com/flwrlabs/flower/tree/main/hub/apps/flowertune-llm) +- [Federated Finetuning of a Vision Transformer](https://github.com/flwrlabs/flower/tree/main/hub/apps/flowertune-vit) +- [Advanced Flower with PyTorch](https://github.com/flwrlabs/flower/tree/main/hub/apps/advanced-pytorch) +- [Comprehensive Flower+XGBoost](https://github.com/flwrlabs/flower/tree/main/hub/apps/xgboost-comprehensive) +- [Flower with KaplanMeierFitter from the lifelines library](https://github.com/flwrlabs/flower/tree/main/hub/apps/federated-kaplan-meier-fitter) +- [Sample Level Privacy with Opacus](https://github.com/flwrlabs/flower/tree/main/hub/apps/opacus) +- [Flower with a Tabular Dataset](https://github.com/flwrlabs/flower/tree/main/hub/apps/fl-tabular) ## Community diff --git a/datasets/README.md b/datasets/README.md index 40f9adf1beb3..6ff444221a6f 100644 --- a/datasets/README.md +++ b/datasets/README.md @@ -10,7 +10,7 @@ Flower Datasets (`flwr-datasets`) is a library to quickly and easily create data > [!TIP] -> For complete documentation that includes API docs, how-to guides and tutorials, please visit the [Flower Datasets Documentation](https://flower.ai/docs/datasets/) and for full FL example see the [Flower Examples page](https://github.com/flwrlabs/flower/tree/main/examples). +> For complete documentation that includes API docs, how-to guides and tutorials, please visit the [Flower Datasets Documentation](https://flower.ai/docs/datasets/) and for full FL example see the [Flower Examples page](https://github.com/flwrlabs/flower/tree/main/hub/apps). ## Installation diff --git a/datasets/docs/source/recommended-fl-datasets.rst b/datasets/docs/source/recommended-fl-datasets.rst index 63b793d5ea0d..1e437eba47cc 100644 --- a/datasets/docs/source/recommended-fl-datasets.rst +++ b/datasets/docs/source/recommended-fl-datasets.rst @@ -5,7 +5,7 @@ This page lists the recommended datasets for federated learning research, which used with Flower Datasets ``flwr-datasets``. To learn about the library, see the `quickstart tutorial `_ . To see the full FL example with Flower and Flower Datasets open the `quickstart-pytorch -`_. +`_. .. note:: diff --git a/dev/devtool/build_example_docs.py b/dev/devtool/build_example_docs.py index 891c242f582e..f33236c41fc3 100644 --- a/dev/devtool/build_example_docs.py +++ b/dev/devtool/build_example_docs.py @@ -195,7 +195,7 @@ def _copy_markdown_files(example: str) -> None: def _add_gh_button(example: str) -> None: gh_text = ( '[View on GitHub]' - f"(https://github.com/flwrlabs/flower/blob/main/examples/{example})" + f"(https://github.com/flwrlabs/flower/blob/main/hub/apps/{example})" ) readme_file = os.path.join(str(ROOT), "examples", "docs", "source", example + ".md") with open(readme_file, "r+", encoding="utf-8") as f: @@ -221,7 +221,7 @@ def _copy_images(example: str) -> None: def _add_all_entries() -> None: - examples_dir = os.path.join(ROOT, "examples") + examples_dir = os.path.join(ROOT, "hub", "apps") for example in sorted(os.listdir(examples_dir)): example_path = os.path.join(examples_dir, example) if os.path.isdir(example_path) and example != "docs": @@ -237,7 +237,7 @@ def _main() -> None: with INDEX.open("w", encoding="utf-8") as index_file: index_file.write(INITIAL_TEXT) - examples_dir = os.path.join(ROOT, "examples") + examples_dir = os.path.join(ROOT, "hub", "apps") for example in sorted(os.listdir(examples_dir)): example_path = os.path.join(examples_dir, example) if os.path.isdir(example_path) and example != "docs": diff --git a/dev/format.sh b/dev/format.sh index feb95c27cbfe..14de26fb5dd4 100755 --- a/dev/format.sh +++ b/dev/format.sh @@ -5,15 +5,15 @@ cd "$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"/ taplo fmt -# Examples -# Iterate over all example directories -for dir in ../examples/*/; do +# Apps +# Iterate over all app directories +for dir in ../hub/apps/*/; do src_args=$(find "$dir" -maxdepth 1 -type d | sed 's/^/--src /' | tr '\n' ' ') python -m isort $dir $src_args --settings-path . & done wait -python -m black -q ../examples -python -m docformatter -i -r ../examples +python -m black -q ../hub +python -m docformatter -i -r ../hub # Benchmarks python -m isort ../benchmarks @@ -22,7 +22,7 @@ python -m docformatter -i -r ../benchmarks # Notebooks KEYS="metadata.celltoolbar metadata.language_info metadata.toc metadata.notify_time metadata.varInspector metadata.accelerator metadata.vscode cell.metadata.id cell.metadata.heading_collapsed cell.metadata.hidden cell.metadata.code_folding cell.metadata.tags cell.metadata.init_cell cell.metadata.vscode cell.metadata.pycharm" -python -m nbstripout ../examples/*/*.ipynb --extra-keys "$KEYS" +python -m nbstripout ../hub/apps/*/*.ipynb --extra-keys "$KEYS" # Markdown -python -m mdformat --number ../examples +python -m mdformat --number ../hub diff --git a/dev/swift-docs-resources/footer.html b/dev/swift-docs-resources/footer.html index 4e8b9b93c46a..46e0dc3c0341 100644 --- a/dev/swift-docs-resources/footer.html +++ b/dev/swift-docs-resources/footer.html @@ -1 +1 @@ - \ No newline at end of file + \ No newline at end of file diff --git a/dev/test.sh b/dev/test.sh index 3f56472f61a3..ca3dda978ca6 100755 --- a/dev/test.sh +++ b/dev/test.sh @@ -9,7 +9,7 @@ echo "- Start Python checks" echo "- isort: start" pids=() -for dir in ../examples/*/; do +for dir in ../hub/apps/*/; do src_args=$(find "$dir" -maxdepth 1 -type d | sed 's/^/--src /' | tr '\n' ' ') python -m isort --check-only $dir $src_args --settings-path . & pids+=($!) @@ -23,7 +23,7 @@ python -m isort --check-only ../benchmarks echo "- isort: done" echo "- black: start" -python -m black --check ../benchmarks ../examples +python -m black --check ../benchmarks ../hub echo "- black: done" echo "- All Python checks passed" @@ -31,7 +31,7 @@ echo "- All Python checks passed" echo "- Start Markdown checks" echo "- mdformat: start" -python -m mdformat --check --number ../examples +python -m mdformat --check --number ../hub echo "- mdformat: done" echo "- All Markdown checks passed" @@ -39,7 +39,7 @@ echo "- All Markdown checks passed" echo "- Start TOML checks" echo "- taplo: start" -taplo fmt --check ../benchmarks ../examples +taplo fmt --check ../benchmarks ../hub echo "- taplo: done" echo "- All TOML checks passed" diff --git a/framework/README.md b/framework/README.md index aa87202bd904..c39a5e4eacac 100644 --- a/framework/README.md +++ b/framework/README.md @@ -113,33 +113,32 @@ Several code examples show different usage scenarios of Flower (in combination w Quickstart examples: -- [Quickstart (TensorFlow)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-tensorflow) -- [Quickstart (PyTorch)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-pytorch) -- [Quickstart (Hugging Face)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-huggingface) -- [Quickstart (PyTorch Lightning)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-pytorch-lightning) -- [Quickstart (fastai)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-fastai) -- [Quickstart (Pandas)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-pandas) -- [Quickstart (JAX)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-jax) -- [Quickstart (MONAI)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-monai) -- [Quickstart (scikit-learn)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-sklearn) -- [Quickstart (Android [TFLite])](https://github.com/flwrlabs/flower/tree/main/examples/android) -- [Quickstart (iOS [CoreML])](https://github.com/flwrlabs/flower/tree/main/examples/ios) -- [Quickstart (MLX)](https://github.com/flwrlabs/flower/tree/main/examples/quickstart-mlx) -- [Quickstart (XGBoost)](https://github.com/flwrlabs/flower/tree/main/examples/xgboost-quickstart) - -Other [examples](https://github.com/flwrlabs/flower/tree/main/examples): - -- [Raspberry Pi & Nvidia Jetson Tutorial](https://github.com/flwrlabs/flower/tree/main/examples/embedded-devices) -- [PyTorch: From Centralized to Federated](https://github.com/flwrlabs/flower/tree/main/examples/pytorch-from-centralized-to-federated) -- [Vertical FL](https://github.com/flwrlabs/flower/tree/main/examples/vertical-fl) -- [Federated Finetuning of OpenAI's Whisper](https://github.com/flwrlabs/flower/tree/main/examples/whisper-federated-finetuning) -- [Federated Finetuning of Large Language Model](https://github.com/flwrlabs/flower/tree/main/examples/flowertune-llm) -- [Federated Finetuning of a Vision Transformer](https://github.com/flwrlabs/flower/tree/main/examples/flowertune-vit) -- [Advanced Flower with PyTorch](https://github.com/flwrlabs/flower/tree/main/examples/advanced-pytorch) -- [Comprehensive Flower+XGBoost](https://github.com/flwrlabs/flower/tree/main/examples/xgboost-comprehensive) -- [Flower with KaplanMeierFitter from the lifelines library](https://github.com/flwrlabs/flower/tree/main/examples/federated-kaplan-meier-fitter) -- [Sample Level Privacy with Opacus](https://github.com/flwrlabs/flower/tree/main/examples/opacus) -- [Flower with a Tabular Dataset](https://github.com/flwrlabs/flower/tree/main/examples/fl-tabular) +- [Quickstart (TensorFlow)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-tensorflow) +- [Quickstart (PyTorch)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-pytorch) +- [Quickstart (Hugging Face)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-huggingface) +- [Quickstart (PyTorch Lightning)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-pytorch-lightning) +- [Quickstart (fastai)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-fastai) +- [Quickstart (Pandas)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-pandas) +- [Quickstart (JAX)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-jax) +- [Quickstart (MONAI)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-monai) +- [Quickstart (scikit-learn)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-sklearn) +- [Quickstart (Android [TFLite])](https://github.com/flwrlabs/flower/tree/main/hub/apps/android) +- [Quickstart (iOS [CoreML])](https://github.com/flwrlabs/flower/tree/main/hub/apps/ios) +- [Quickstart (MLX)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-mlx) +- [Quickstart (XGBoost)](https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-xgboost) + +Other [examples](https://github.com/flwrlabs/flower/tree/main/hub/apps): + +- [Raspberry Pi & Nvidia Jetson Tutorial](https://github.com/flwrlabs/flower/tree/main/hub/apps/embedded-devices) +- [Vertical FL](https://github.com/flwrlabs/flower/tree/main/hub/apps/vertical-fl) +- [Federated Finetuning of OpenAI's Whisper](https://github.com/flwrlabs/flower/tree/main/hub/apps/whisper-federated-finetuning) +- [Federated Finetuning of Large Language Model](https://github.com/flwrlabs/flower/tree/main/hub/apps/flowertune-llm) +- [Federated Finetuning of a Vision Transformer](https://github.com/flwrlabs/flower/tree/main/hub/apps/flowertune-vit) +- [Advanced Flower with PyTorch](https://github.com/flwrlabs/flower/tree/main/hub/apps/advanced-pytorch) +- [Comprehensive Flower+XGBoost](https://github.com/flwrlabs/flower/tree/main/hub/apps/xgboost-comprehensive) +- [Flower with KaplanMeierFitter from the lifelines library](https://github.com/flwrlabs/flower/tree/main/hub/apps/federated-kaplan-meier-fitter) +- [Sample Level Privacy with Opacus](https://github.com/flwrlabs/flower/tree/main/hub/apps/opacus) +- [Flower with a Tabular Dataset](https://github.com/flwrlabs/flower/tree/main/hub/apps/fl-tabular) ## Community diff --git a/framework/dev/update_version.py b/framework/dev/update_version.py index 6efb4f3c8e5d..d05fa64bb169 100644 --- a/framework/dev/update_version.py +++ b/framework/dev/update_version.py @@ -24,7 +24,7 @@ } EXAMPLES = { - "examples/**/pyproject.toml": [ + "hub/apps/**/pyproject.toml": [ "flwr[simulation]>={version}", "flwr[simulation]=={version}", "flwr>={version}", diff --git a/framework/docs/source/contributor-how-to-set-up-a-virtual-env.rst b/framework/docs/source/contributor-how-to-set-up-a-virtual-env.rst index a86304c6f961..de15b2d364da 100644 --- a/framework/docs/source/contributor-how-to-set-up-a-virtual-env.rst +++ b/framework/docs/source/contributor-how-to-set-up-a-virtual-env.rst @@ -25,8 +25,8 @@ Flower requires at least `Python 3.10 `_. One of the recommended virtual environment is `pyenv `_/`virtualenv -`_. Please see `Flower examples -`_ for details. +`_. Please see `Flower apps +`_ for details. Once Pyenv is set up, you can use it to install `Python Version 3.10 `_ or above: diff --git a/framework/docs/source/docker/run-quickstart-examples-docker-compose.rst b/framework/docs/source/docker/run-quickstart-examples-docker-compose.rst index 48dfe497f231..fcf88b2dbdc5 100644 --- a/framework/docs/source/docker/run-quickstart-examples-docker-compose.rst +++ b/framework/docs/source/docker/run-quickstart-examples-docker-compose.rst @@ -7,7 +7,7 @@ #################################################### Flower provides a set of `quickstart examples -`_ to help you get started with +`_ to help you get started with the framework. These examples are designed to demonstrate the capabilities of Flower and by default run using the Simulation Runtime. This guide demonstrates how to run them using Flower's Deployment Runtime via Docker Compose. @@ -36,7 +36,7 @@ Before you start, make sure that: .. code-block:: bash $ git clone --depth=1 https://github.com/flwrlabs/flower.git \ - && mv flower/examples/quickstart-pytorch . \ + && mv flower/hub/apps/quickstart-pytorch . \ && rm -rf flower && cd quickstart-pytorch 2. Download the `compose.yml diff --git a/framework/docs/source/docker/tutorial-deploy-on-multiple-machines.rst b/framework/docs/source/docker/tutorial-deploy-on-multiple-machines.rst index f0d0cf36a931..7a0d1f0e1f0d 100644 --- a/framework/docs/source/docker/tutorial-deploy-on-multiple-machines.rst +++ b/framework/docs/source/docker/tutorial-deploy-on-multiple-machines.rst @@ -88,7 +88,7 @@ For example, you can use ``scp`` to copy the directories: $ scp -r ./server \ ./superlink-certificates \ - ../../../examples/quickstart-sklearn/pyproject.toml remote:~/distributed + ../../../hub/apps/quickstart-sklearn/pyproject.toml remote:~/distributed ******************************************** Step 3: Start the Flower Server Components @@ -135,7 +135,7 @@ On your local machine, run the following command to start the client components: .. code-block:: bash # In the `docker/distributed` directory - $ export PROJECT_DIR=../../../../examples/quickstart-sklearn + $ export PROJECT_DIR=../../../../hub/apps/quickstart-sklearn $ docker compose -f client/compose.yml up --build -d .. note:: @@ -175,8 +175,8 @@ Run the project and follow the ``ServerApp`` logs: .. code-block:: bash - $ cd flower/examples/quickstart-sklearn - $ flwr run ../../../examples/quickstart-sklearn remote-deployment --stream + $ cd flower/hub/apps/quickstart-sklearn + $ flwr run ../../../hub/apps/quickstart-sklearn remote-deployment --stream That's it! With these steps, you've set up Flower on two separate machines and are ready to start using it. @@ -200,6 +200,6 @@ Shut down the Flower server components and delete the SuperLink state: $ cd $ docker compose -f server/compose.yml down -v -.. |quickstart_sklearn_tabular| replace:: ``examples/quickstart-sklearn`` +.. |quickstart_sklearn_tabular| replace:: ``hub/apps/quickstart-sklearn`` -.. _quickstart_sklearn_tabular: https://github.com/flwrlabs/flower/tree/main/examples/quickstart-sklearn +.. _quickstart_sklearn_tabular: https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-sklearn diff --git a/framework/docs/source/explanation-federated-evaluation.rst b/framework/docs/source/explanation-federated-evaluation.rst index 69a297e87a2a..2ec810eb9998 100644 --- a/framework/docs/source/explanation-federated-evaluation.rst +++ b/framework/docs/source/explanation-federated-evaluation.rst @@ -232,5 +232,5 @@ arbitrary evaluation results as a dictionary: For a full code example that uses both centralized and federated evaluation, see the `Advanced PyTorch Example -`_ (the same +`_ (the same approach can be applied to workloads implemented in any other framework). diff --git a/framework/docs/source/how-to-authenticate-supernodes.rst b/framework/docs/source/how-to-authenticate-supernodes.rst index 9e191e4e8a30..639b6ff25d81 100644 --- a/framework/docs/source/how-to-authenticate-supernodes.rst +++ b/framework/docs/source/how-to-authenticate-supernodes.rst @@ -51,7 +51,7 @@ enabled: .. tip:: Checkout the `Flower Authentication - `_ + `_ example for a complete self-contained example on how to setup TLS and node authentication. diff --git a/framework/docs/source/how-to-enable-tls-connections.rst b/framework/docs/source/how-to-enable-tls-connections.rst index 750fd06c5900..0953e7ec2a55 100644 --- a/framework/docs/source/how-to-enable-tls-connections.rst +++ b/framework/docs/source/how-to-enable-tls-connections.rst @@ -19,7 +19,7 @@ This guide describes how to establish secure TLS Superlink ↔ SuperNodes as wel .. tip:: Checkout the `Flower Authentication - `_ + `_ example for a complete self-contained example on how to setup TLS and (optionally) node authentication. Check out the :doc:`how-to-authenticate-supernodes` guide to learn more about adding an authentication layer to SuperLink ↔ SuperNode diff --git a/framework/docs/source/how-to-migrate-from-openfl.rst b/framework/docs/source/how-to-migrate-from-openfl.rst index b581a41a030f..829e990633cd 100644 --- a/framework/docs/source/how-to-migrate-from-openfl.rst +++ b/framework/docs/source/how-to-migrate-from-openfl.rst @@ -545,7 +545,7 @@ given deep learning framework (in this case PyTorch) due to the saving of a fina This functionality is optional, but mirrors the automatic saving of a model at the end of an OpenFL experiment. This ``ServerApp`` change requires only a few lines of modifications, and Flower has support for an extensive set of deep learning frameworks -in it's `examples `_ (Tensorflow, +in its `examples `_ (Tensorflow, FastAI, Huggingface, etc.) should you need reference code. ************** diff --git a/framework/docs/source/how-to-run-simulations.rst b/framework/docs/source/how-to-run-simulations.rst index 1f17dba545f6..e25728693519 100644 --- a/framework/docs/source/how-to-run-simulations.rst +++ b/framework/docs/source/how-to-run-simulations.rst @@ -126,18 +126,18 @@ Tutorial `_, `quickstart JAX Tutorial simulation-ready. - `Quickstart TensorFlow/Keras - `_. + `_. - `Quickstart PyTorch - `_ + `_ - `Advanced PyTorch - `_ + `_ - `Quickstart MLX - `_ + `_ - `ViT fine-tuning - `_ + `_ The complete list of examples can be found in `the Flower GitHub -`_. +`_. .. _clientappresources: diff --git a/framework/docs/source/how-to-save-and-load-model-checkpoints.rst b/framework/docs/source/how-to-save-and-load-model-checkpoints.rst index d9574ebdcf7b..cb5778740180 100644 --- a/framework/docs/source/how-to-save-and-load-model-checkpoints.rst +++ b/framework/docs/source/how-to-save-and-load-model-checkpoints.rst @@ -106,4 +106,4 @@ Then, pass it to the |strategy_start_link|_ method of the defined strategy: ) If you are interested, checkout the details in `Advanced PyTorch Example -`_. +`_. diff --git a/framework/docs/source/how-to-upgrade-to-flower-1.0.rst b/framework/docs/source/how-to-upgrade-to-flower-1.0.rst index 83c6bdc8ed37..46cb466bfe9b 100644 --- a/framework/docs/source/how-to-upgrade-to-flower-1.0.rst +++ b/framework/docs/source/how-to-upgrade-to-flower-1.0.rst @@ -139,7 +139,7 @@ that just became possible: ************** Most official `Flower code examples -`_ are already updated to Flower +`_ are already updated to Flower 1.0, they can serve as a reference for using the Flower 1.0 API. If there are further questions, `join the Flower Slack `_ and use the channel ``#questions``. diff --git a/framework/docs/source/how-to-upgrade-to-message-api.rst b/framework/docs/source/how-to-upgrade-to-message-api.rst index 9985934efb16..a06ea46981a6 100644 --- a/framework/docs/source/how-to-upgrade-to-message-api.rst +++ b/framework/docs/source/how-to-upgrade-to-message-api.rst @@ -63,7 +63,7 @@ Let's dive in! If you would like to create a new Flower App using the `Message API`, run the ``flwr new`` command and choose the appropriate template. Alternatively, you may want to take a look at the `quickstart-pytorch - `_ + `_ example. ******************** diff --git a/framework/docs/source/how-to-use-differential-privacy.rst b/framework/docs/source/how-to-use-differential-privacy.rst index b72baed53ed8..7c9a624333f0 100644 --- a/framework/docs/source/how-to-use-differential-privacy.rst +++ b/framework/docs/source/how-to-use-differential-privacy.rst @@ -195,4 +195,4 @@ Local Training using Privacy Engines For ensuring data instance-level privacy during local model training on the client side, consider leveraging privacy engines such as Opacus. For examples of using Flower with these engines, please refer to the Flower examples directory (`Opacus -`_). +`_). diff --git a/framework/docs/source/how-to-use-strategies.rst b/framework/docs/source/how-to-use-strategies.rst index fdf829fd1f8f..60c8988f3d8f 100644 --- a/framework/docs/source/how-to-use-strategies.rst +++ b/framework/docs/source/how-to-use-strategies.rst @@ -310,6 +310,6 @@ of this callback is and how to use it: .. tip:: Take a look at the `quickstart-pytorch - `_ example + `_ example on GitHub for a complete example using several of the concepts presented in this how-to guide. diff --git a/framework/docs/source/ref-example-projects.rst b/framework/docs/source/ref-example-projects.rst index 89be99adb862..d9f21d692ee8 100644 --- a/framework/docs/source/ref-example-projects.rst +++ b/framework/docs/source/ref-example-projects.rst @@ -17,7 +17,7 @@ The TensorFlow/Keras quickstart example shows CIFAR-10 image classification with MobileNetV2: - `Quickstart TensorFlow (Code) - `_ + `_ - :doc:`Quickstart TensorFlow (Tutorial) ` - `Quickstart TensorFlow (Blog Post) `_ @@ -30,18 +30,9 @@ The PyTorch quickstart example shows CIFAR-10 image classification with a simple Convolutional Neural Network: - `Quickstart PyTorch (Code) - `_ + `_ - :doc:`Quickstart PyTorch (Tutorial) ` -**************************************** - PyTorch: From Centralized To Federated -**************************************** - -This example shows how a regular PyTorch project can be federated using Flower: - -- `PyTorch: From Centralized To Federated (Code) - `_ - ****************************************************** Federated Learning on Raspberry Pi and Nvidia Jetson ****************************************************** @@ -50,6 +41,6 @@ This example shows how Flower can be used to build a federated learning system t across Raspberry Pi and Nvidia Jetson: - `Federated Learning on Raspberry Pi and Nvidia Jetson (Code) - `_ + `_ - `Federated Learning on Raspberry Pi and Nvidia Jetson (Blog Post) `_ diff --git a/framework/docs/source/ref-faq.rst b/framework/docs/source/ref-faq.rst index 1feeb322924c..1fa59da044aa 100644 --- a/framework/docs/source/ref-faq.rst +++ b/framework/docs/source/ref-faq.rst @@ -7,7 +7,7 @@ Flower. .. dropdown:: :fa:`eye,mr-1` How can I run Federated Learning on a Raspberry Pi? - Find the `blog post about federated learning on embedded device here `_ and the corresponding `GitHub code example `_. + Find the `blog post about federated learning on embedded device here `_ and the corresponding `GitHub code example `_. .. dropdown:: :fa:`eye,mr-1` Does Flower support federated learning on Android devices? diff --git a/framework/docs/source/tutorial-quickstart-android.rst b/framework/docs/source/tutorial-quickstart-android.rst index 6391f6a099e7..4ffe07ea3886 100644 --- a/framework/docs/source/tutorial-quickstart-android.rst +++ b/framework/docs/source/tutorial-quickstart-android.rst @@ -18,4 +18,4 @@ Let's build a federated learning system using TFLite and Flower on Android! Please refer to the `full code example -`_ to learn more. +`_ to learn more. diff --git a/framework/docs/source/tutorial-quickstart-fastai.rst b/framework/docs/source/tutorial-quickstart-fastai.rst index 9f5ebd71fed3..6c7483b8f9a0 100644 --- a/framework/docs/source/tutorial-quickstart-fastai.rst +++ b/framework/docs/source/tutorial-quickstart-fastai.rst @@ -17,7 +17,7 @@ Then, clone the code example directly from GitHub: .. code-block:: shell git clone --depth=1 https://github.com/flwrlabs/flower.git _tmp \ - && mv _tmp/examples/quickstart-fastai . \ + && mv _tmp/hub/apps/quickstart-fastai . \ && rm -rf _tmp && cd quickstart-fastai This will create a new directory called `quickstart-fastai` containing the following @@ -102,5 +102,5 @@ in ``pyproject.toml`` like this: .. note:: Check the `source code - `_ of this - tutorial in ``examples/quickstart-fastai`` in the Flower GitHub repository. + `_ of this + tutorial in ``hub/apps/quickstart-fastai`` in the Flower GitHub repository. diff --git a/framework/docs/source/tutorial-quickstart-huggingface.rst b/framework/docs/source/tutorial-quickstart-huggingface.rst index 1e1d8938a932..5847b2bb1ca3 100644 --- a/framework/docs/source/tutorial-quickstart-huggingface.rst +++ b/framework/docs/source/tutorial-quickstart-huggingface.rst @@ -383,7 +383,7 @@ for an LLM. of a federated fine-tuning of an LLM with Flower, refer to the |flowertune|_ example in the Flower GitHub repository. -.. |quickstart_hf_link| replace:: ``examples/quickstart-huggingface`` +.. |quickstart_hf_link| replace:: ``hub/apps/quickstart-huggingface`` .. |fedavg| replace:: ``FedAvg`` @@ -403,13 +403,13 @@ for an LLM. .. _flowerdatasets: https://flower.ai/docs/datasets/ -.. _flowertune: https://github.com/flwrlabs/flower/tree/main/examples/flowertune-llm +.. _flowertune: https://github.com/flwrlabs/flower/tree/main/hub/apps/flowertune-llm .. _iidpartitioner: https://flower.ai/docs/datasets/ref-api/flwr_datasets.partitioner.IidPartitioner.html#flwr_datasets.partitioner.IidPartitioner .. _otherpartitioners: https://flower.ai/docs/datasets/ref-api/flwr_datasets.partitioner.html -.. _quickstart_hf_link: https://github.com/flwrlabs/flower/tree/main/examples/quickstart-huggingface +.. _quickstart_hf_link: https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-huggingface .. |arrayrecord_link| replace:: ``ArrayRecord`` diff --git a/framework/docs/source/tutorial-quickstart-ios.rst b/framework/docs/source/tutorial-quickstart-ios.rst index 612240b66ac1..4c47a30c1101 100644 --- a/framework/docs/source/tutorial-quickstart-ios.rst +++ b/framework/docs/source/tutorial-quickstart-ios.rst @@ -91,7 +91,7 @@ Let's create a new application project in Xcode and add ``flwr`` as a dependency project. For our application, we will store the logic of our app in ``FLiOSModel.swift`` and the UI elements in ``ContentView.swift``. We will focus more on ``FLiOSModel.swift`` in this quickstart. Please refer to the `full code example -`_ to learn more about the +`_ to learn more about the app. Import Flower and CoreML related packages in ``FLiOSModel.swift``: @@ -189,5 +189,5 @@ Simulator visit `here Congratulations! You've successfully built and run your first federated learning system in your ios device. The full `source code -`_ for this example can be -found in ``examples/ios``. +`_ for this example can be +found in ``hub/apps/ios``. diff --git a/framework/docs/source/tutorial-quickstart-jax.rst b/framework/docs/source/tutorial-quickstart-jax.rst index 4dab4659dea8..b5b0d2cd8114 100644 --- a/framework/docs/source/tutorial-quickstart-jax.rst +++ b/framework/docs/source/tutorial-quickstart-jax.rst @@ -435,9 +435,9 @@ for JAX with Flower! .. _otherpartitioners: https://flower.ai/docs/datasets/ref-api/flwr_datasets.partitioner.html -.. |quickstart_jax_link| replace:: ``examples/quickstart-jax`` +.. |quickstart_jax_link| replace:: ``hub/apps/quickstart-jax`` -.. _quickstart_jax_link: https://github.com/flwrlabs/flower/tree/main/examples/quickstart-jax +.. _quickstart_jax_link: https://github.com/flwrlabs/flower/tree/main/hub/apps/quickstart-jax .. |message_link| replace:: ``Message`` diff --git a/framework/docs/source/tutorial-quickstart-mlx.rst b/framework/docs/source/tutorial-quickstart-mlx.rst index 1732b32b1a3b..318b48c74cb1 100644 --- a/framework/docs/source/tutorial-quickstart-mlx.rst +++ b/framework/docs/source/tutorial-quickstart-mlx.rst @@ -459,6 +459,6 @@ Congratulations! You've successfully built and run your first federated learning .. note:: Check the `source code - `_ of the - extended version of this tutorial in ``examples/quickstart-mlx`` in the Flower + `_ of the + extended version of this tutorial in ``hub/apps/quickstart-mlx`` in the Flower GitHub repository. diff --git a/framework/docs/source/tutorial-quickstart-pandas.rst b/framework/docs/source/tutorial-quickstart-pandas.rst index 98500016c1ed..3e27eda7faeb 100644 --- a/framework/docs/source/tutorial-quickstart-pandas.rst +++ b/framework/docs/source/tutorial-quickstart-pandas.rst @@ -10,5 +10,5 @@ Let's build a federated analytics system using Pandas and Flower! Please refer to the `full code example -`_ to learn +`_ to learn more. diff --git a/framework/docs/source/tutorial-quickstart-pytorch-lightning.rst b/framework/docs/source/tutorial-quickstart-pytorch-lightning.rst index 209d26c932ef..d3a98a80fd11 100644 --- a/framework/docs/source/tutorial-quickstart-pytorch-lightning.rst +++ b/framework/docs/source/tutorial-quickstart-pytorch-lightning.rst @@ -18,7 +18,7 @@ Then, clone the code example directly from GitHub: .. code-block:: shell git clone --depth=1 https://github.com/flwrlabs/flower.git _tmp \ - && mv _tmp/examples/quickstart-pytorch-lightning . \ + && mv _tmp/hub/apps/quickstart-pytorch-lightning . \ && rm -rf _tmp && cd quickstart-pytorch-lightning This will create a new directory called `quickstart-pytorch-lightning` containing the @@ -111,8 +111,8 @@ in ``pyproject.toml`` like this: .. note:: Check the `source code - `_ - of this tutorial in ``examples/quickstart-pytorch-lightning`` in the Flower GitHub + `_ + of this tutorial in ``hub/apps/quickstart-pytorch-lightning`` in the Flower GitHub repository. .. |fedavg| replace:: ``FedAvg`` diff --git a/framework/docs/source/tutorial-quickstart-pytorch.rst b/framework/docs/source/tutorial-quickstart-pytorch.rst index e646c12832fe..30bf67f12949 100644 --- a/framework/docs/source/tutorial-quickstart-pytorch.rst +++ b/framework/docs/source/tutorial-quickstart-pytorch.rst @@ -428,6 +428,6 @@ Congratulations! You've successfully built and run your first federated learning .. note:: Check the `source code - `_ of the - extended version of this tutorial in ``examples/quickstart-pytorch`` in the Flower + `_ of the + extended version of this tutorial in ``hub/apps/quickstart-pytorch`` in the Flower GitHub repository. diff --git a/framework/docs/source/tutorial-quickstart-scikitlearn.rst b/framework/docs/source/tutorial-quickstart-scikitlearn.rst index a3c7606e49d0..87e556b2b8d1 100644 --- a/framework/docs/source/tutorial-quickstart-scikitlearn.rst +++ b/framework/docs/source/tutorial-quickstart-scikitlearn.rst @@ -351,7 +351,7 @@ in scikit-learn on the Iris dataset using the new Message API. Check the source code of another Flower App using ``scikit-learn`` in the `Flower GitHub repository - `_. + `_. .. |flowerdatasets| replace:: Flower Datasets @@ -361,7 +361,7 @@ in scikit-learn on the Iris dataset using the new Message API. .. |otherpartitioners| replace:: other partitioners -.. |quickstart_sklearn_link| replace:: ``examples/sklearn-logreg-mnist`` +.. |quickstart_sklearn_link| replace:: ``hub/apps/sklearn-logreg-mnist`` .. _client: ref-api/flwr.client.Client.html#client diff --git a/framework/docs/source/tutorial-quickstart-tensorflow.rst b/framework/docs/source/tutorial-quickstart-tensorflow.rst index e37427072975..532a6823868e 100644 --- a/framework/docs/source/tutorial-quickstart-tensorflow.rst +++ b/framework/docs/source/tutorial-quickstart-tensorflow.rst @@ -364,6 +364,6 @@ Congratulations! You've successfully built and run your first federated learning Check the source code of the extended version of this tutorial in |quickstart_tf_link|_ in the Flower GitHub repository. -.. |quickstart_tf_link| replace:: ``examples/quickstart-tensorflow`` +.. |quickstart_tf_link| replace:: ``hub/apps/quickstart-tensorflow`` -.. _quickstart_tf_link: https://github.com/flwrlabs/flower/blob/main/examples/quickstart-tensorflow +.. _quickstart_tf_link: https://github.com/flwrlabs/flower/blob/main/hub/apps/quickstart-tensorflow diff --git a/framework/docs/source/tutorial-quickstart-xgboost.rst b/framework/docs/source/tutorial-quickstart-xgboost.rst index 5b14177d7f36..9c48a5266bc3 100644 --- a/framework/docs/source/tutorial-quickstart-xgboost.rst +++ b/framework/docs/source/tutorial-quickstart-xgboost.rst @@ -442,6 +442,6 @@ Congratulations! You've successfully built and run your first federated learning .. note:: Check the `source code - `_ of the - extended version of this tutorial in ``examples/xgboost-quickstart`` in the Flower + `_ of the + extended version of this tutorial in ``hub/apps/quickstart-xgboost`` in the Flower GitHub repository. diff --git a/framework/swift/flwr/README.md b/framework/swift/flwr/README.md index f5e46c21fb6c..a30449fcbb23 100644 --- a/framework/swift/flwr/README.md +++ b/framework/swift/flwr/README.md @@ -8,7 +8,7 @@ You can download the Flower project and integrate the package manually. ## Usage -A comprehensive example is available in: [`examples/ios/`](https://github.com/flwrlabs/flower/tree/main/examples/ios). To give information about the usage structurally: +A comprehensive example is available in: [`hub/apps/ios/`](https://github.com/flwrlabs/flower/tree/main/hub/apps/ios). To give information about the usage structurally: ``` import flwr diff --git a/glossary/edge-computing.mdx b/glossary/edge-computing.mdx index d5090ec70a20..d340626fadad 100644 --- a/glossary/edge-computing.mdx +++ b/glossary/edge-computing.mdx @@ -37,4 +37,4 @@ When deploying federated learning systems, edge computing is an important compon ### Edge Computing with Flower -With the Flower framework, you can easily deploy federated learning workflows and maximise the use of edge computing resources. Flower provides the infrastructure to perform federated learning, federated evaluation, and federated analytics, all in a easy, scalable and secure way. Start with our tutorial on running Federated Learning on Embedded Devices (link [here](https://github.com/flwrlabs/flower/tree/main/examples/embedded-devices)), which shows you how to run Flower on NVidia Jetson devices and Raspberry Pis as your edge compute. +With the Flower framework, you can easily deploy federated learning workflows and maximise the use of edge computing resources. Flower provides the infrastructure to perform federated learning, federated evaluation, and federated analytics, all in a easy, scalable and secure way. Start with our tutorial on running Federated Learning on Embedded Devices (link [here](https://github.com/flwrlabs/flower/tree/main/hub/apps/embedded-devices)), which shows you how to run Flower on NVidia Jetson devices and Raspberry Pis as your edge compute. diff --git a/examples/.gitignore b/hub/apps/.gitignore similarity index 100% rename from examples/.gitignore rename to hub/apps/.gitignore diff --git a/examples/advanced-pytorch/.gitignore b/hub/apps/advanced-pytorch/.gitignore similarity index 100% rename from examples/advanced-pytorch/.gitignore rename to hub/apps/advanced-pytorch/.gitignore diff --git a/examples/advanced-pytorch/README.md b/hub/apps/advanced-pytorch/README.md similarity index 100% rename from examples/advanced-pytorch/README.md rename to hub/apps/advanced-pytorch/README.md diff --git a/examples/advanced-pytorch/_static/fmnist_50_lda.png b/hub/apps/advanced-pytorch/_static/fmnist_50_lda.png similarity index 100% rename from examples/advanced-pytorch/_static/fmnist_50_lda.png rename to hub/apps/advanced-pytorch/_static/fmnist_50_lda.png diff --git a/examples/advanced-pytorch/_static/wandb_plots.png b/hub/apps/advanced-pytorch/_static/wandb_plots.png similarity index 100% rename from examples/advanced-pytorch/_static/wandb_plots.png rename to hub/apps/advanced-pytorch/_static/wandb_plots.png diff --git a/examples/advanced-pytorch/pyproject.toml b/hub/apps/advanced-pytorch/pyproject.toml similarity index 100% rename from examples/advanced-pytorch/pyproject.toml rename to hub/apps/advanced-pytorch/pyproject.toml diff --git a/examples/advanced-pytorch/pytorch_example/__init__.py b/hub/apps/advanced-pytorch/pytorch_example/__init__.py similarity index 100% rename from examples/advanced-pytorch/pytorch_example/__init__.py rename to hub/apps/advanced-pytorch/pytorch_example/__init__.py diff --git a/examples/advanced-pytorch/pytorch_example/client_app.py b/hub/apps/advanced-pytorch/pytorch_example/client_app.py 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b/hub/apps/custom-mods/custom_mods/task.py similarity index 100% rename from examples/custom-mods/custom_mods/task.py rename to hub/apps/custom-mods/custom_mods/task.py diff --git a/examples/custom-mods/pyproject.toml b/hub/apps/custom-mods/pyproject.toml similarity index 100% rename from examples/custom-mods/pyproject.toml rename to hub/apps/custom-mods/pyproject.toml diff --git a/hub/apps/demo/README.md b/hub/apps/demo/README.md new file mode 100644 index 000000000000..bc7d6ca671fc --- /dev/null +++ b/hub/apps/demo/README.md @@ -0,0 +1,72 @@ +--- +tags: [quickstart] +dataset: [] +framework: [numpy] +--- + +# Federated Learning with NumPy and Flower (Demo) + +This example of Flower uses a dummy `NumPy` model as well as dummy training and evaluation steps in the `ClientApp` to showcase the core functionality of Flower apps. This app does not use a dataset. + +## Set up the project + +### Fetch the app + +Install Flower: + +```shell +pip install flwr +``` + +Fetch the app: + +```shell +flwr new @flwrlabs/demo +``` + +```shell +demo +├── quickstart_numpy +│ ├── __init__.py +│ ├── client_app.py # Defines your ClientApp +│ ├── server_app.py # Defines your ServerApp +│ └── task.py # Defines model creation +├── pyproject.toml # Project metadata like dependencies and configs +└── README.md +``` + +### Install dependencies and project + +Install the dependencies defined in `pyproject.toml` as well as the `quickstart_numpy` package. + +```bash +pip install -e . +``` + +> **Tip:** Your `pyproject.toml` file can define more than just the dependencies of your Flower app. You can also use it to specify hyperparameters for your runs and control which Flower Runtime is used. By default, it uses the Simulation Runtime, but you can switch to the Deployment Runtime when needed. +> Learn more in the [TOML configuration guide](https://flower.ai/docs/framework/how-to-configure-pyproject-toml.html). + +## Run with the Simulation Engine + +In the `quickstart-numpy` directory, use `flwr run` to run a local simulation: + +```bash +flwr run . +``` + +Refer to the [How to Run Simulations](https://flower.ai/docs/framework/how-to-run-simulations.html) guide in the documentation for advice on how to optimize your simulations. + +## Run with the Deployment Engine + +Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be interested in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation. + +You can run Flower on Docker too! Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation. + +## Resources + +- Flower website: [flower.ai](https://flower.ai/) +- Check the documentation: [flower.ai/docs](https://flower.ai/docs/) +- Give Flower a ⭐️ on GitHub: [GitHub](https://github.com/adap/flower) +- Join the Flower community! + - [Flower Slack](https://flower.ai/join-slack/) + - [Flower Discuss](https://discuss.flower.ai/) diff --git a/hub/apps/demo/pyproject.toml b/hub/apps/demo/pyproject.toml new file mode 100644 index 000000000000..8edae513fdf3 --- /dev/null +++ b/hub/apps/demo/pyproject.toml @@ -0,0 +1,35 @@ +# ===================================================================== +# For a full TOML configuration guide, check the Flower docs: +# https://flower.ai/docs/framework/how-to-configure-pyproject-toml.html +# ===================================================================== + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "demo" +version = "1.1.0" +description = "Federated Learning with Numpy and Flower (Demo)" +license = "Apache-2.0" +# Dependencies for your Flower App +dependencies = [ + "flwr[simulation]>=1.26.1", + "numpy>=2.0.2", +] + +[tool.hatch.build.targets.wheel] +packages = ["."] + +[tool.flwr.app] +publisher = "flwrlabs" + +# Point to your ServerApp and ClientApp objects +# Format: ":" +[tool.flwr.app.components] +serverapp = "quickstart_numpy.server_app:app" +clientapp = "quickstart_numpy.client_app:app" + +# Custom config values accessible via `context.run_config` +[tool.flwr.app.config] +num-server-rounds = 3 diff --git a/hub/apps/demo/quickstart_numpy/__init__.py b/hub/apps/demo/quickstart_numpy/__init__.py new file mode 100644 index 000000000000..670a5448e97c --- /dev/null +++ b/hub/apps/demo/quickstart_numpy/__init__.py @@ -0,0 +1 @@ +"""@flwrlabs/demo: A Flower Hub Demo app.""" diff --git a/hub/apps/demo/quickstart_numpy/client_app.py b/hub/apps/demo/quickstart_numpy/client_app.py new file mode 100644 index 000000000000..22678378c9e1 --- /dev/null +++ b/hub/apps/demo/quickstart_numpy/client_app.py @@ -0,0 +1,46 @@ +"""@flwrlabs/demo: A Flower Hub Demo app.""" + +import numpy as np +from flwr.app import ArrayRecord, Context, Message, MetricRecord, RecordDict +from flwr.clientapp import ClientApp + +# Flower ClientApp +app = ClientApp() + + +@app.train() +def train(msg: Message, context: Context): + """Train the model on local data.""" + + # The model is the global arrays + ndarrays = msg.content["arrays"].to_numpy_ndarrays() + + # Simulate local training (here we just add random noise to model parameters) + model = [m + np.random.rand(*m.shape) for m in ndarrays] + + # Construct and return reply Message + model_record = ArrayRecord(model) + metrics = { + "random_metric": np.random.rand(), + "num-examples": 1, + } + metric_record = MetricRecord(metrics) + content = RecordDict({"arrays": model_record, "metrics": metric_record}) + return Message(content=content, reply_to=msg) + + +@app.evaluate() +def evaluate(msg: Message, context: Context): + """Evaluate the model on local data.""" + + # The model is the global arrays + ndarrays = msg.content["arrays"].to_numpy_ndarrays() + + # Return reply Message + metrics = { + "random_metric": np.random.rand(3).tolist(), + "num-examples": 1, + } + metric_record = MetricRecord(metrics) + content = RecordDict({"metrics": metric_record}) + return Message(content=content, reply_to=msg) diff --git a/hub/apps/demo/quickstart_numpy/server_app.py b/hub/apps/demo/quickstart_numpy/server_app.py new file mode 100644 index 000000000000..a4bfdfa4c53c --- /dev/null +++ b/hub/apps/demo/quickstart_numpy/server_app.py @@ -0,0 +1,33 @@ +"""@flwrlabs/demo: A Flower Hub Demo app.""" + +import numpy as np +from flwr.app import ArrayRecord, Context +from flwr.serverapp import Grid, ServerApp +from flwr.serverapp.strategy import FedAvg + +from quickstart_numpy.task import get_dummy_model + +# Create ServerApp +app = ServerApp() + + +@app.main() +def main(grid: Grid, context: Context) -> None: + """Main entry point for the ServerApp.""" + + # Read run config + num_rounds: int = context.run_config["num-server-rounds"] + + # Load global model + model = get_dummy_model() + arrays = ArrayRecord(model) + + # Initialize FedAvg strategy + strategy = FedAvg() + + # Start strategy, run FedAvg for `num_rounds` + result = strategy.start( + grid=grid, + initial_arrays=arrays, + num_rounds=num_rounds, + ) diff --git a/hub/apps/demo/quickstart_numpy/task.py b/hub/apps/demo/quickstart_numpy/task.py new file mode 100644 index 000000000000..0252ab0d8d40 --- /dev/null +++ b/hub/apps/demo/quickstart_numpy/task.py @@ -0,0 +1,7 @@ +"""@flwrlabs/demo: A Flower Hub Demo app.""" + +import numpy as np + + +def get_dummy_model(): + return [np.ones((1, 1))] diff --git a/examples/embedded-devices/README.md b/hub/apps/embedded-devices/README.md similarity index 100% rename from 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