diff --git a/README.md b/README.md index 24ce6ff3..7ac78e2d 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,9 @@ + +> [!NOTE] +> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。 +> [English](./README.en.md) · [原始项目](https://github.com/tensorflow/tensorflow) · [上游 README](https://github.com/tensorflow/tensorflow/blob/HEAD/README.md) +> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。 +
@@ -16,62 +22,37 @@ ------------------- | [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) | -[TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform -for machine learning. It has a comprehensive, flexible ecosystem of -[tools](https://www.tensorflow.org/resources/tools), -[libraries](https://www.tensorflow.org/resources/libraries-extensions), and -[community](https://www.tensorflow.org/community) resources that lets -researchers push the state-of-the-art in ML and developers easily build and -deploy ML-powered applications. +[TensorFlow](https://www.tensorflow.org/) 是一个端到端的开源机器学习平台。它拥有全面且灵活的生态系统，涵盖[工具](https://www.tensorflow.org/resources/tools),、[库](https://www.tensorflow.org/resources/libraries-extensions),和[社区](https://www.tensorflow.org/community)资源，使研究人员能够推动机器学习（ML）的最前沿发展，也让开发者能够轻松构建和部署基于 ML 的应用。 -TensorFlow was originally developed by researchers and engineers working within -the Machine Intelligence team at Google Brain to conduct research in machine -learning and neural networks. However, the framework is versatile enough to be -used in other areas as well. +TensorFlow 最初由 Google Brain 旗下机器智能团队的研究人员和工程师开发，旨在开展机器学习和神经网络研究。不过，该框架功能广泛，足以应用于其他领域。 -TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python) -and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a -non-guaranteed backward compatible API for -[other languages](https://www.tensorflow.org/api_docs). +TensorFlow 提供稳定的 [Python](https://www.tensorflow.org/api_docs/python) 和 [C++](https://www.tensorflow.org/api_docs/cc) API，以及不保证向后兼容的[其他语言](https://www.tensorflow.org/api_docs). API。 -Keep up-to-date with release announcements and security updates by subscribing -to -[announce@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce). -See all the [mailing lists](https://www.tensorflow.org/community/forums). +订阅 [announce@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce). 以获取最新的发布公告和安全更新。查看所有[邮件列表](https://www.tensorflow.org/community/forums).。 -## Install +## 安装 -See the [TensorFlow install guide](https://www.tensorflow.org/install) for the -[pip package](https://www.tensorflow.org/install/pip), to -[enable GPU support](https://www.tensorflow.org/install/gpu), use a -[Docker container](https://www.tensorflow.org/install/docker), and -[build from source](https://www.tensorflow.org/install/source). +请参阅 [TensorFlow 安装指南](https://www.tensorflow.org/install)，了解如何使用 [pip 包](https://www.tensorflow.org/install/pip),、[启用 GPU 支持](https://www.tensorflow.org/install/gpu),、使用 [Docker 容器](https://www.tensorflow.org/install/docker),以及[从源码构建](https://www.tensorflow.org/install/source).。 -To install the current release, which includes support for -[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and -Windows)*: +安装当前版本（包含对[支持 CUDA 的 GPU 显卡](https://www.tensorflow.org/install/gpu)的支持 *（Ubuntu 和 Windows）*）： ``` pip install tensorflow ``` -Other devices (DirectX and MacOS-metal) are supported using -[Device Plugins](https://www.tensorflow.org/install/gpu_plugins#available_devices). +其他设备（DirectX 和 MacOS-metal）可通过[设备插件](https://www.tensorflow.org/install/gpu_plugins#available_devices).获得支持。 -A smaller CPU-only TensorFlow package is also available: +另外也提供了一个更小的仅支持 CPU 的 TensorFlow 包： ``` pip install tensorflow-cpu ``` -To update TensorFlow to the latest version, add the `--upgrade` flag to the -commands above. +要将 TensorFlow 更新到最新版本，请在上面的命令中添加 `--upgrade` 标志。 -*Nightly binaries are available for testing using the -[tf-nightly](https://pypi.python.org/pypi/tf-nightly) and -[tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) packages on PyPI.* +*用于测试的每日构建版本可通过 PyPI 上的 [tf-nightly](https://pypi.python.org/pypi/tf-nightly) 和 [tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) 包获取。* -#### *Try your first TensorFlow program* +#### *尝试你的第一个 TensorFlow 程序* ```shell $ python @@ -86,83 +67,68 @@ $ python b'Hello, TensorFlow!' ``` -For more examples, see the -[TensorFlow Tutorials](https://www.tensorflow.org/tutorials/). +更多示例请参阅 [TensorFlow 教程](https://www.tensorflow.org/tutorials/).。 -## Contribution guidelines +## 贡献指南 -**If you want to contribute to TensorFlow, be sure to review the -[Contribution Guidelines](CONTRIBUTING.md). This project adheres to TensorFlow's -[Code of Conduct](CODE_OF_CONDUCT.md). By participating, you are expected to -uphold this code.** +**如果你想为 TensorFlow 做贡献，请务必阅读[贡献指南](CONTRIBUTING.md)。本项目遵循 TensorFlow 的[行为准则](CODE_OF_CONDUCT.md)。参与即表示你同意遵守该准则。** -**We use [GitHub Issues](https://github.com/tensorflow/tensorflow/issues) for -tracking requests and bugs, please see -[TensorFlow Forum](https://discuss.tensorflow.org/) for general questions and -discussion, and please direct specific questions to -[Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow).** +**我们使用 [GitHub Issues](https://github.com/tensorflow/tensorflow/issues) 来跟踪需求和错误，请访问 [TensorFlow 论坛](https://discuss.tensorflow.org/) 进行一般性讨论和问答，具体问题请到 [Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow).** 上提问。** -The TensorFlow project strives to abide by generally accepted best practices in -open-source software development. +TensorFlow 项目致力于遵循开源软件开发中公认的最佳实践。 -## Patching guidelines +## 补丁指南 -Follow these steps to patch a specific version of TensorFlow, for example, to -apply fixes to bugs or security vulnerabilities: +按照以下步骤为特定版本的 TensorFlow 打补丁，例如修复错误或安全漏洞： -* Clone the TensorFlow repository and switch to the appropriate branch for - your desired version—for example, `r2.8` for version 2.8. -* Apply the desired changes (i.e., cherry-pick them) and resolve any code - conflicts. -* Run TensorFlow tests and ensure they pass. -* [Build](https://www.tensorflow.org/install/source) the TensorFlow pip - package from source. +* 克隆 TensorFlow 仓库并切换到所需版本的相应分支——例如，版本 2.8 使用 `r2.8` 分支。 +* 应用所需的更改（即 cherry-pick），并解决所有代码冲突。 +* 运行 TensorFlow 测试并确保通过。 +* 从源码[构建](https://www.tensorflow.org/install/source) TensorFlow pip 包。 -## Continuous build status +## 持续构建状态 -You can find more community-supported platforms and configurations in the -[TensorFlow SIG Build Community Builds Table](https://github.com/tensorflow/build#community-supported-tensorflow-builds). +你可以在 [TensorFlow SIG Build 社区构建表](https://github.com/tensorflow/build#community-supported-tensorflow-builds). 中找到更多社区支持的平台和配置。 -### Official Builds +### 官方构建 -Build Type | Status | Artifacts +构建类型 | 状态 | 制品 ----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- **Linux CPU** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.html) | [PyPI](https://pypi.org/project/tf-nightly/) **Linux GPU** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-gpu-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-gpu-py3.html) | [PyPI](https://pypi.org/project/tf-nightly-gpu/) -**Linux XLA** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.html) | TBA +**Linux XLA** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.html) | 待定 **macOS** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/macos-py2-cc.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/macos-py2-cc.html) | [PyPI](https://pypi.org/project/tf-nightly/) **Windows CPU** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-cpu.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-cpu.html) | [PyPI](https://pypi.org/project/tf-nightly/) **Windows GPU** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-gpu.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-gpu.html) | [PyPI](https://pypi.org/project/tf-nightly-gpu/) -**Android** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/android.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/android.html) | [Download](https://bintray.com/google/tensorflow/tensorflow/_latestVersion) -**Raspberry Pi 0 and 1** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv6l.whl) -**Raspberry Pi 2 and 3** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl) +**Android** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/android.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/android.html) | [下载](https://bintray.com/google/tensorflow/tensorflow/_latestVersion) +**Raspberry Pi 0 和 1** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv6l.whl) +**Raspberry Pi 2 和 3** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl) -## Resources +## 资源 -* [TensorFlow.org](https://www.tensorflow.org) -* [TensorFlow Tutorials](https://www.tensorflow.org/tutorials/) -* [TensorFlow Official Models](https://github.com/tensorflow/models/tree/master/official) -* [TensorFlow Examples](https://github.com/tensorflow/examples) -* [TensorFlow Codelabs](https://codelabs.developers.google.com/?cat=TensorFlow) -* [TensorFlow Blog](https://blog.tensorflow.org) -* [Learn ML with TensorFlow](https://www.tensorflow.org/resources/learn-ml) -* [TensorFlow Twitter](https://twitter.com/tensorflow) -* [TensorFlow YouTube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ) -* [TensorFlow model optimization roadmap](https://www.tensorflow.org/model_optimization/guide/roadmap) -* [TensorFlow White Papers](https://www.tensorflow.org/about/bib) -* [TensorBoard Visualization Toolkit](https://github.com/tensorflow/tensorboard) -* [TensorFlow Code Search](https://cs.opensource.google/tensorflow/tensorflow) +* [TensorFlow.org](https://www.tensorflow.org)) +* [TensorFlow 教程](https://www.tensorflow.org/tutorials/)) +* [TensorFlow 官方模型](https://github.com/tensorflow/models/tree/master/official)) +* [TensorFlow 示例](https://github.com/tensorflow/examples)) +* [TensorFlow 编程实练](https://codelabs.developers.google.com/?cat=TensorFlow)) +* [TensorFlow 博客](https://blog.tensorflow.org)) +* [用 TensorFlow 学习机器学习](https://www.tensorflow.org/resources/learn-ml)) +* [TensorFlow Twitter](https://twitter.com/tensorflow)) +* [TensorFlow YouTube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ)) +* [TensorFlow 模型优化路线图](https://www.tensorflow.org/model_optimization/guide/roadmap)) +* [TensorFlow 白皮书](https://www.tensorflow.org/about/bib)) +* [TensorBoard 可视化工具包](https://github.com/tensorflow/tensorboard)) +* [TensorFlow 代码搜索](https://cs.opensource.google/tensorflow/tensorflow)) -Learn more about the -[TensorFlow Community](https://www.tensorflow.org/community) and how to -[Contribute](https://www.tensorflow.org/community/contribute). +了解更多关于 [TensorFlow 社区](https://www.tensorflow.org/community)) 的信息，以及如何 [贡献代码](https://www.tensorflow.org/community/contribute).)。 -## Courses +## 课程 -* [Coursera](https://www.coursera.org/search?query=TensorFlow) -* [Udacity](https://www.udacity.com/courses/all?search=TensorFlow) -* [Edx](https://www.edx.org/search?q=TensorFlow) +* [Coursera](https://www.coursera.org/search?query=TensorFlow)) +* [Udacity](https://www.udacity.com/courses/all?search=TensorFlow)) +* [Edx](https://www.edx.org/search?q=TensorFlow)) -## License +## 许可 [Apache License 2.0](LICENSE) +USD 预算：$0/$3；剩余 $3