docs: make Chinese README the default

2026-07-13 07:53:44 +00:00
parent 7202ee4749
commit 0d55876139
1 changed files with 58 additions and 92 deletions
@@ -1,3 +1,9 @@
+<!-- WEHUB_ZH_README -->
+> [!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。
+
 <div align="center">
  <img src="https://www.tensorflow.org/images/tf_logo_horizontal.png">
 </div>
@@ -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