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https://github.com/xitu/tensorflow-docs

TensorFlow 最新官方文档中文版
https://github.com/xitu/tensorflow-docs

documentation machine-learning tensorflow

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TensorFlow 最新官方文档中文版

Host: GitHub
URL: https://github.com/xitu/tensorflow-docs
Owner: xitu
Created: 2018-03-08T09:39:54.000Z (over 6 years ago)
Default Branch: zh-hans
Last Pushed: 2019-04-17T08:38:29.000Z (about 5 years ago)
Last Synced: 2024-05-02T01:09:16.967Z (about 2 months ago)
Topics: documentation, machine-learning, tensorflow
Language: Jupyter Notebook
Homepage: https://tensorflow.juejin.im
Size: 4.56 MB
Stars: 3,815
Watchers: 179
Forks: 475
Open Issues: 2
Metadata Files:
- Readme: README.md

Lists

awesome-stars - xitu/tensorflow-docs
awesome - xitu/tensorflow-docs - TensorFlow 最新官方文档中文版 (Jupyter Notebook)
awesome-ml-summary - TensorFlow-cn - cn](https://tensorflow.juejin.im/get_started/)| (1 Predict / Machine Learning Related Documention)
awesome-stars - tensorflow-docs - TensorFlow 最新官方文档中文版 V1.10 (Jupyter Notebook)
awesome-stars - xitu/tensorflow-docs - `★3814` TensorFlow 最新官方文档中文版 (Jupyter Notebook)
awesome-stars - tensorflow-docs - TensorFlow 最新官方文档中文版 (Jupyter Notebook)
awesome - xitu/tensorflow-docs - TensorFlow 最新官方文档中文版 (Jupyter Notebook)

README

        


  





> [TensorFlow Docs](https://github.com/xitu/tensorflow-docs) 是由[掘金翻译计划](https://github.com/xitu/gold-miner)实时维护的 TensorFlow 官方文档中文版，维护者为全球各大公司开发人员和各著名高校研究者及学生。欢迎大家加入维护团队，欢迎提 Issue 和 PR，参与之前请阅读[文档维护说明](https://github.com/xitu/tensorflow-docs/wiki#%E6%96%87%E6%A1%A3%E7%BB%B4%E6%8A%A4%E8%A7%84%E8%8C%83)。

>

> - 阅读文档请到 👉 https://tensorflow.juejin.im

> - 推荐学习顺序等更多内容详见：[TensorFlow Docs WIKI](https://github.com/xitu/tensorflow-docs/wiki)

> - 相关术语表：[TensorFlow 术语表](https://github.com/xitu/tensorflow-docs/wiki/TensorFlow-%E6%9C%AF%E8%AF%AD%E8%A1%A8)，[人工智能术语表](https://github.com/xitu/tensorflow-docs/wiki#%E6%9C%AF%E8%AF%AD%E8%A1%A8)

> - 掘金翻译计划欢迎大家的加入，详见 👉 [加入我们](https://github.com/xitu/gold-miner)

---

| **`Documentation`** |

|-----------------|

| [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) |

**TensorFlow** 是一个使用数据流图进行数值计算开源软件库。图的节点表示数学运算，节点之间的边表示流动的多维数据数组（张量）。这种灵活的架构使你能在无需重写代码的情况下，将计算在桌面端、服务端或移动端部署到一个或多个 CPU 和 GPU 中。TensorFlow 还包含 [TensorBoard](https://www.tensorflow.org/guide/summaries_and_tensorboard)，它是一个数据可视化工具包。

TensorFlow 最初由 Google 机器智能研究机构内的 Google Brain 团队的研究人员和工程师开发，用于进行机器学习和深度神经网络研究。此系统一般足以适用于各种其他领域。

TensorFlow 提供了稳定的 Python API 和 C 语言 API，以及没有向后兼容性保证的如 C++、Go、Java、JavaScript 和 Swift 等 API。

你可以通过订阅 [[email protected]](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce) 来及时获得 TensorFlow 最新的公告及更新等信息。

## 安装

**在 [安装 TensorFlow](https://www.tensorflow.org/install) 页面中查看关于稳定二进制版的安装或从源码安装的安装步骤。**

喜欢挑战的人也可以尝试我们的开发版：

**开发版 pip 包**

* 我们非常高兴发布 TensorFlow 的开发版，现在 pypi 提供开发版的 pip 包 [tf-nightly](https://pypi.python.org/pypi/tf-nightly) 和

  [tf-nightly-gpu](https://pypi.python.org/pypi/tf-nightly-gpu) 项目。在干净的环境中简单运行 `pip install tf-nightly` 或 `pip install tf-nightly-gpu` 即可安装 TensorFlow 开发版。 我们为 Linux、Mac 和 Windows 提供  CPU 和 GPU 支持。

#### 开启你的第一个 TensorFlow 程序

```shell

$ python

```

```python

>>> import tensorflow as tf

>>> tf.enable_eager_execution()

>>> tf.add(1, 2)

3

>>> hello = tf.constant('Hello, TensorFlow!')

>>> hello.numpy()

'Hello, TensorFlow!'

```

在 [tensorflow.org 的教程页面](https://www.tensorflow.org/tutorials/)中了解更多有关如何在 TensorFlow 中执行特定任务的示例吧。

## 贡献指南

**如果你想参与贡献 TensorFlow，请先查看我们的 [贡献指南](CONTRIBUTING.md)。此项目遵循 TensorFlow

[项目规范](CODE_OF_CONDUCT.md)。我们期望你能遵循此规范。**

**我们还使用 [GitHub issues](https://github.com/tensorflow/tensorflow/issues) 来跟进 requests 和 bugs。对于一般性问题和讨论请查看 

[TensorFlow 讨论](https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss)，或直接在 [Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow) 提问。**

TensorFlow 项目致力于遵守开源软件开发中普遍接受的最佳实践：

[![CII 最佳实践](https://bestpractices.coreinfrastructure.org/projects/1486/badge)](https://bestpractices.coreinfrastructure.org/projects/1486)

## 持续构建状态

### 官方构建

| Build Type      | Status | Artifacts |

| ---             | ---    | ---       |

| **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 |

| **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://api.bintray.com/packages/google/tensorflow/tensorflow/images/download.svg)](https://bintray.com/google/tensorflow/tensorflow/_latestVersion) |

| **Raspberry Pi 0 and 1** | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py2.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py2.html) [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.html) | [Py2](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp27-none-linux_armv6l.whl) [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-py2.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py2.html) [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html) | [Py2](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp27-none-linux_armv7l.whl) [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl) |

### 社区支持下的构建

| Build Type      | Status | Artifacts |

| ---             | ---    | ---       |

| **IBM s390x**       | [![Build Status](http://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_CI/badge/icon)](http://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_CI/) | TBA |

| **IBM ppc64le CPU** | [![Build Status](http://powerci.osuosl.org/job/TensorFlow_Ubuntu_16.04_CPU/badge/icon)](http://powerci.osuosl.org/job/TensorFlow_Ubuntu_16.04_CPU/) | TBA |

| **IBM ppc64le GPU** | [![Build Status](http://powerci.osuosl.org/job/TensorFlow_Ubuntu_16.04_PPC64LE_GPU/badge/icon)](http://powerci.osuosl.org/job/TensorFlow_Ubuntu_16.04_PPC64LE_GPU/) | TBA |

| **Linux CPU with Intel® MKL-DNN** Nightly | [![Build Status](https://tensorflow-ci.intel.com/job/tensorflow-mkl-linux-cpu/badge/icon)](https://tensorflow-ci.intel.com/job/tensorflow-mkl-linux-cpu/) | [Nightly](https://tensorflow-ci.intel.com/job/tensorflow-mkl-build-whl-nightly/) |

| **Linux CPU with Intel® MKL-DNN** Python 2.7
 **Linux CPU with Intel® MKL-DNN** Python 3.5
  **Linux CPU with Intel® MKL-DNN** Python 3.6 | [![Build Status](https://tensorflow-ci.intel.com/job/tensorflow-mkl-build-release-whl/badge/icon)](https://tensorflow-ci.intel.com/job/tensorflow-mkl-build-release-whl/lastStableBuild)|[1.10.0 py2.7](https://storage.googleapis.com/intel-optimized-tensorflow/tensorflow-1.10.0-cp27-cp27mu-linux_x86_64.whl)
[1.10.0 py3.5](https://storage.googleapis.com/intel-optimized-tensorflow/tensorflow-1.10.0-cp35-cp35m-linux_x86_64.whl)
[1.10.0 py3.6](https://storage.googleapis.com/intel-optimized-tensorflow/tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl) |

## 更多信息

* [TensorFlow 网站](https://www.tensorflow.org)

* [TensorFlow 教程](https://www.tensorflow.org/tutorials/)

* [TensorFlow 模型](https://github.com/tensorflow/models)

* [TensorFlow Twitter](https://twitter.com/tensorflow)

* [TensorFlow Blog](https://medium.com/tensorflow)

* [TensorFlow Course at Stanford](https://web.stanford.edu/class/cs20si)

* [TensorFlow Roadmap](https://www.tensorflow.org/community/roadmap)

* [TensorFlow White Papers](https://www.tensorflow.org/about/bib)

* [TensorFlow YouTube Channel](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ)

你可以在 [tensorflow.org 社区页](https://www.tensorflow.org/community) 了解更多关于参与 TensorFlow 社区的方法。

## 文档管理团队

| [
_LeviDing](https://github.com/leviding)
[👀](#review-leviding "Reviewed Pull Requests") [🌍](#translation-leviding "Translation") [📋](#eventOrganizing-leviding "Event Organizing") | [
_pkuwwt](https://github.com/pkuwwt)
[👀](#review-pkuwwt "Reviewed Pull Requests") [🌍](#translation-pkuwwt "Translation") | [
_{John Jiang}](https://github.com/JohnJiangLA)
[👀](#review-JohnJiangLA "Reviewed Pull Requests") [🌍](#translation-JohnJiangLA "Translation") | [
_lsvih](https://github.com/lsvih)
[👀](#review-lsvih "Reviewed Pull Requests") [🌍](#translation-lsvih "Translation") | [
_foxxnuaa](https://github.com/foxxnuaa)
[👀](#review-foxxnuaa "Reviewed Pull Requests") [🌍](#translation-foxxnuaa "Translation") | [
_changkun](https://github.com/changkun)
[👀](#review-changkun "Reviewed Pull Requests") [🌍](#translation-changkun "Translation") |

|:-:|:-:|:-:|:-:|:-:|:-:|

## Co-Translators

[所有译者详细信息](https://github.com/xitu/tensorflow-docs/graphs/contributors)

## 文档维护支持

[](https://juejin.im)

## 许可

文档正在完善中，未经允许禁止任何形式的转载。

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