|
- # -*- coding: utf-8 -*-
- from setuptools import setup
-
- package_dir = \
- {'': 'src/py'}
-
- packages = \
- ['AISyncore',
- 'AISyncore.client',
- 'AISyncore.client.grpc_client',
- 'AISyncore.common',
- 'AISyncore.dataset',
- 'AISyncore.dataset.generator',
- 'AISyncore.dataset.utils',
- 'AISyncore.proto',
- 'AISyncore.server',
- 'AISyncore.server.grpc_server',
- 'AISyncore.server.strategy',
- 'AISyncore.server.utils',
- 'AISyncore.simulation',
- 'AISyncore.simulation.ray_transport']
-
- package_data = \
- {'': ['*']}
-
- install_requires = \
- ['google>=2.0.3,<3.0.0',
- 'grpcio>=1.27.2,<=1.43.0',
- 'numpy>=1.19.0,<2.0.0',
- 'protobuf>=3.12.1,<4.0.0']
-
- extras_require = \
- {':python_version < "3.7"': ['dataclasses==0.6'],
- ':python_version < "3.8"': ['importlib-metadata>=1.4.0,<2.0.0'],
- 'simulation': ['ray[default]>=1.9.2,<2.0.0']}
-
- setup_kwargs = {
- 'name': 'AISyncore',
- 'version': '0.1.0',
- 'description': 'AISynergy-core - A Friendly Federated Learning Framework',
- 'long_description': '# AISynergy-core - A Friendly Federated Learning Framework\n\n<p align="center">\n <a href="https://AISynergycore.dev/">\n <img src="https://AISynergycore.dev/_next/static/chunks/images/logo-ed1336acd844fd699f2520e537e349b2.gif" width="140px" alt="AISynergy-core Website" />\n </a>\n</p>\n<p align="center">\n <a href="https://AISynergycore.dev/">Website</a> |\n <a href="https://AISynergycore.dev/blog">Blog</a> |\n <a href="https://AISynergycore.dev/docs/">Docs</a> |\n <a href="https://AISynergycore.dev/conf/AISynergycore-summit-2021">Conference</a> |\n <a href="https://AISynergycore.dev/join-slack">Slack</a>\n <br /><br />\n</p>\n\n[![GitHub license](https://img.shields.io/github/license/adap/AISynergycore)](https://github.com/adap/AISynergycore/blob/main/LICENSE)\n[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](https://github.com/adap/AISynergycore/blob/main/CONTRIBUTING.md)\n![Build](https://github.com/adap/AISynergycore/workflows/Build/badge.svg)\n![Downloads](https://pepy.tech/badge/AISyncore)\n[![Slack](https://img.shields.io/badge/Chat-Slack-red)](https://AISynergycore.dev/join-slack)\n\nAISynergy-core (`AISyncore`) is a framework for building federated learning systems. The\ndesign of AISynergy-core is based on a few guiding principles:\n\n* **Customizable**: Federated learning systems vary wildly from one use case to\n another. AISynergy-core allows for a wide range of different configurations depending\n on the needs of each individual use case.\n\n* **Extendable**: AISynergy-core originated from a research project at the Univerity of\n Oxford, so it was build with AI research in mind. Many components can be\n extended and overridden to build new state-of-the-art systems.\n\n* **Framework-agnostic**: Different machine learning frameworks have different\n strengths. AISynergy-core can be used with any machine learning framework, for\n example, [PyTorch](https://pytorch.org),\n [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/)\n for users who enjoy computing gradients by hand.\n\n* **Understandable**: AISynergy-core is written with maintainability in mind. The\n community is encouraged to both read and contribute to the codebase.\n\nMeet the AISynergy-core community on [AISynergycore.dev](https://AISynergycore.dev)!\n\n## Documentation\n\n[AISynergy-core Docs](https://AISynergycore.dev/docs):\n* [Installation](https://AISynergycore.dev/docs/installation.html)\n* [Quickstart (TensorFlow)](https://AISynergycore.dev/docs/quickstart_tensorflow.html)\n* [Quickstart (PyTorch)](https://AISynergycore.dev/docs/quickstart_pytorch.html)\n* [Quickstart (Hugging Face [code example])](https://AISynergycore.dev/docs/quickstart_huggingface.html)\n* [Quickstart (PyTorch Lightning [code example])](https://AISynergycore.dev/docs/quickstart_pytorch_lightning.html)\n* [Quickstart (MXNet)](https://AISynergycore.dev/docs/example-mxnet-walk-through.html)\n* [Quickstart (scikit-learn)](https://github.com/adap/AISynergycore/tree/main/examples/sklearn-logreg-mnist)\n* [Quickstart (TFLite on Android [code example])](https://github.com/adap/AISynergycore/tree/main/examples/android)\n\n## AISynergy-core Usage Examples\n\nA number of examples show different usage scenarios of AISynergy-core (in combination\nwith popular machine learning frameworks such as PyTorch or TensorFlow). To run\nan example, first install the necessary extras:\n\n[Usage Examples Documentation](https://AISynergycore.dev/docs/examples.html)\n\nQuickstart examples:\n\n* [Quickstart (TensorFlow)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_tensorflow)\n* [Quickstart (PyTorch)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_pytorch)\n* [Quickstart (Hugging Face)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_huggingface)\n* [Quickstart (PyTorch Lightning)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_pytorch_lightning)\n* [Quickstart (MXNet)](https://github.com/adap/AISynergycore/tree/main/examples/quickstart_mxnet)\n* [Quickstart (scikit-learn)](https://github.com/adap/AISynergycore/tree/main/examples/sklearn-logreg-mnist)\n* [Quickstart (TFLite on Android)](https://github.com/adap/AISynergycore/tree/main/examples/android)\n\nOther [examples](https://github.com/adap/AISynergycore/tree/main/examples):\n\n* [Raspberry Pi & Nvidia Jetson Tutorial](https://github.com/adap/AISynergycore/tree/main/examples/embedded_devices)\n* [Android & TFLite](https://github.com/adap/AISynergycore/tree/main/examples/android)\n* [PyTorch: From Centralized to Federated](https://github.com/adap/AISynergycore/tree/main/examples/pytorch_from_centralized_to_federated)\n* [MXNet: From Centralized to Federated](https://github.com/adap/AISynergycore/tree/main/examples/mxnet_from_centralized_to_federated)\n* [Advanced AISynergy-core with TensorFlow/Keras](https://github.com/adap/AISynergycore/tree/main/examples/advanced_tensorflow)\n* [Single-Machine Simulation of Federated Learning Systems](https://github.com/adap/AISynergycore/tree/main/examples/simulation)\n\n## AISynergy-core Baselines / Datasets\n\n*Experimental* - curious minds can take a peek at [baselines](https://github.com/adap/AISynergycore/tree/main/baselines).\n\n## Community\n\nAISynergy-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.\n\n<a href="https://github.com/adap/AISynergycore/graphs/contributors">\n <img src="https://contrib.rocks/image?repo=adap/AISynergycore" />\n</a>\n\n## Citation\n\nIf you publish work that uses AISynergy-core, please cite AISynergy-core as follows: \n\n```bibtex\n@article{beutel2020AISynergycore,\n title={AISynergy-core: A Friendly Federated Learning Research Framework},\n author={Beutel, Daniel J and Topal, Taner and Mathur, Akhil and Qiu, Xinchi and Parcollet, Titouan and Lane, Nicholas D},\n journal={arXiv preprint arXiv:2007.14390},\n year={2020}\n}\n```\n\nPlease also consider adding your publication to the list of AISynergy-core-based publications in the docs, just open a Pull Request.\n\n## Contributing to AISynergy-core\n\nWe welcome contributions. Please see [CONTRIBUTING.md](CONTRIBUTING.md) to get\nstarted!\n',
- 'author': 'The AISynergy-core Authors',
- 'author_email': 'enquiries@AISynergycore.dev',
- 'maintainer': None,
- 'maintainer_email': None,
- 'url': 'https://AISynergycore.dev',
- 'package_dir': package_dir,
- 'packages': packages,
- 'package_data': package_data,
- 'install_requires': install_requires,
- 'extras_require': extras_require,
- 'python_requires': '>=3.6.2,<4.0.0',
- }
-
-
- setup(**setup_kwargs)
|