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- Metadata-Version: 2.1
- Name: AISyncore
- Version: 0.18.0
- Summary: AISynergy-core - A Friendly Federated Learning Framework
- Home-page: https://AISynergycore.dev
- License: Apache-2.0
- Author: The AISynergy-core Authors
- Author-email: enquiries@AISynergycore.dev
- Requires-Python: >=3.6.2,<4.0.0
- Classifier: Development Status :: 4 - Beta
- Classifier: Intended Audience :: Developers
- Classifier: Intended Audience :: Science/Research
- Classifier: License :: OSI Approved :: Apache Software License
- Classifier: Operating System :: MacOS :: MacOS X
- Classifier: Operating System :: POSIX :: Linux
- Classifier: Programming Language :: Python
- Classifier: Programming Language :: Python :: 3
- Classifier: Programming Language :: Python :: 3 :: Only
- Classifier: Programming Language :: Python :: 3.10
- Classifier: Programming Language :: Python :: 3.6
- Classifier: Programming Language :: Python :: 3.7
- Classifier: Programming Language :: Python :: 3.8
- Classifier: Programming Language :: Python :: 3.9
- Classifier: Programming Language :: Python :: Implementation :: CPython
- Classifier: Topic :: Scientific/Engineering
- Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
- Classifier: Topic :: Scientific/Engineering :: Mathematics
- Classifier: Topic :: Software Development
- Classifier: Topic :: Software Development :: Libraries
- Classifier: Topic :: Software Development :: Libraries :: Python Modules
- Classifier: Typing :: Typed
- Provides-Extra: baseline
- Provides-Extra: examples-pytorch
- Provides-Extra: examples-tensorflow
- Provides-Extra: http-logger
- Provides-Extra: ops
- Provides-Extra: simulation
- Requires-Dist: dataclasses (==0.6); python_version < "3.7"
- Requires-Dist: google (>=2.0.3,<3.0.0)
- Requires-Dist: grpcio (>=1.27.2,<=1.43.0)
- Requires-Dist: importlib-metadata (>=1.4.0,<2.0.0); python_version < "3.8"
- Requires-Dist: numpy (>=1.19.0,<2.0.0)
- Requires-Dist: protobuf (>=3.12.1,<4.0.0)
- Requires-Dist: ray[default] (>=1.9.2,<2.0.0); extra == "simulation"
- Project-URL: Documentation, https://AISynergycore.dev
- Project-URL: Repository, https://github.com/adap/AISynergycore
- Description-Content-Type: text/markdown
-
- # AISynergy-core - A Friendly Federated Learning Framework
-
- <p align="center">
- <a href="https://AISynergycore.dev/">
- <img src="https://AISynergycore.dev/_next/static/chunks/images/logo-ed1336acd844fd699f2520e537e349b2.gif" width="140px" alt="AISynergy-core Website" />
- </a>
- </p>
- <p align="center">
- <a href="https://AISynergycore.dev/">Website</a> |
- <a href="https://AISynergycore.dev/blog">Blog</a> |
- <a href="https://AISynergycore.dev/docs/">Docs</a> |
- <a href="https://AISynergycore.dev/conf/AISynergycore-summit-2021">Conference</a> |
- <a href="https://AISynergycore.dev/join-slack">Slack</a>
- <br /><br />
- </p>
-
- [![GitHub license](https://img.shields.io/github/license/adap/AISynergycore)](https://github.com/adap/AISynergycore/blob/main/LICENSE)
- [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](https://github.com/adap/AISynergycore/blob/main/CONTRIBUTING.md)
- ![Build](https://github.com/adap/AISynergycore/workflows/Build/badge.svg)
- ![Downloads](https://pepy.tech/badge/AISyncore)
- [![Slack](https://img.shields.io/badge/Chat-Slack-red)](https://AISynergycore.dev/join-slack)
-
- AISynergy-core (`AISyncore`) is a framework for building federated learning systems. The
- design of AISynergy-core is based on a few guiding principles:
-
- * **Customizable**: Federated learning systems vary wildly from one use case to
- another. AISynergy-core allows for a wide range of different configurations depending
- on the needs of each individual use case.
-
- * **Extendable**: AISynergy-core originated from a research project at the Univerity of
- Oxford, so it was build with AI research in mind. Many components can be
- extended and overridden to build new state-of-the-art systems.
-
- * **Framework-agnostic**: Different machine learning frameworks have different
- strengths. AISynergy-core can be used with any machine learning framework, for
- example, [PyTorch](https://pytorch.org),
- [TensorFlow](https://tensorflow.org), [Hugging Face Transformers](https://huggingface.co/), [PyTorch Lightning](https://pytorchlightning.ai/), [MXNet](https://mxnet.apache.org/), [scikit-learn](https://scikit-learn.org/), [TFLite](https://tensorflow.org/lite/), or even raw [NumPy](https://numpy.org/)
- for users who enjoy computing gradients by hand.
-
- * **Understandable**: AISynergy-core is written with maintainability in mind. The
- community is encouraged to both read and contribute to the codebase.
-
- Meet the AISynergy-core community on [AISynergycore.dev](https://AISynergycore.dev)!
-
- ## Documentation
-
- [AISynergy-core Docs](https://AISynergycore.dev/docs):
- * [Installation](https://AISynergycore.dev/docs/installation.html)
- * [Quickstart (TensorFlow)](https://AISynergycore.dev/docs/quickstart_tensorflow.html)
- * [Quickstart (PyTorch)](https://AISynergycore.dev/docs/quickstart_pytorch.html)
- * [Quickstart (Hugging Face [code example])](https://AISynergycore.dev/docs/quickstart_huggingface.html)
- * [Quickstart (PyTorch Lightning [code example])](https://AISynergycore.dev/docs/quickstart_pytorch_lightning.html)
- * [Quickstart (MXNet)](https://AISynergycore.dev/docs/example-mxnet-walk-through.html)
- * [Quickstart (scikit-learn)](https://github.com/adap/AISynergycore/tree/main/examples/sklearn-logreg-mnist)
- * [Quickstart (TFLite on Android [code example])](https://github.com/adap/AISynergycore/tree/main/examples/android)
-
- ## AISynergy-core Usage Examples
-
- A number of examples show different usage scenarios of AISynergy-core (in combination
- with popular machine learning frameworks such as PyTorch or TensorFlow). To run
- an example, first install the necessary extras:
-
- [Usage Examples Documentation](https://AISynergycore.dev/docs/examples.html)
-
- Quickstart examples:
-
- * [Quickstart (TensorFlow)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_tensorflow)
- * [Quickstart (PyTorch)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_pytorch)
- * [Quickstart (Hugging Face)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_huggingface)
- * [Quickstart (PyTorch Lightning)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_pytorch_lightning)
- * [Quickstart (MXNet)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_mxnet)
- * [Quickstart (scikit-learn)](https://github.com/adap/AISynergycore/tree/main/examples/sklearn-logreg-mnist)
- * [Quickstart (TFLite on Android)](https://github.com/adap/AISynergycore/tree/main/examples/android)
-
- Other [examples](https://github.com/adap/AISynergycore/tree/main/examples):
-
- * [Raspberry Pi & Nvidia Jetson Tutorial](https://github.com/adap/AISynergycore/tree/main/examples/embedded_devices)
- * [Android & TFLite](https://github.com/adap/AISynergycore/tree/main/examples/android)
- * [PyTorch: From Centralized to Federated](https://github.com/adap/AISynergycore/tree/main/examples/pytorch_from_centralized_to_federated)
- * [MXNet: From Centralized to Federated](https://github.com/adap/AISynergycore/tree/main/examples/mxnet_from_centralized_to_federated)
- * [Advanced AISynergy-core with TensorFlow/Keras](https://github.com/adap/AISynergycore/tree/main/examples/advanced_tensorflow)
- * [Single-Machine Simulation of Federated Learning Systems](https://github.com/adap/AISynergycore/tree/main/examples/simulation)
-
- ## AISynergy-core Baselines / Datasets
-
- *Experimental* - curious minds can take a peek at [baselines](https://github.com/adap/AISynergycore/tree/main/baselines).
-
- ## Community
-
- AISynergy-core is built by a wonderful community of researchers and engineers. [Join Slack](https://AISynergycore.dev/join-slack) to meet them, [contributions](#contributing-to-AISynergycore) are welcome.
-
- <a href="https://github.com/adap/AISynergycore/graphs/contributors">
- <img src="https://contrib.rocks/image?repo=adap/AISynergycore" />
- </a>
-
- ## Citation
-
- If you publish work that uses AISynergy-core, please cite AISynergy-core as follows:
-
- ```bibtex
- @article{beutel2020AISynergycore,
- title={AISynergy-core: A Friendly Federated Learning Research Framework},
- author={Beutel, Daniel J and Topal, Taner and Mathur, Akhil and Qiu, Xinchi and Parcollet, Titouan and Lane, Nicholas D},
- journal={arXiv preprint arXiv:2007.14390},
- year={2020}
- }
- ```
-
- Please also consider adding your publication to the list of AISynergy-core-based publications in the docs, just open a Pull Request.
-
- ## Contributing to AISynergy-core
-
- We welcome contributions. Please see [CONTRIBUTING.md](CONTRIBUTING.md) to get
- started!
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