开源软件名称：

tensorflow

开源软件地址：

https://gitee.com/mirrors/tensorflow

开源软件介绍：

`Documentation`

TensorFlow is an end-to-end open source platformfor machine learning. It has a comprehensive, flexible ecosystem oftools,libraries, andcommunity resources that letsresearchers push the state-of-the-art in ML and developers easily build anddeploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working on theGoogle Brain team within Google's Machine Intelligence Research organization toconduct machine learning and deep neural networks research. The system isgeneral enough to be applicable in a wide variety of other domains, as well.

TensorFlow provides stable Pythonand C++ APIs, as well asnon-guaranteed backward compatible API forother languages.

Keep up-to-date with release announcements and security updates by subscribingto[email protected].See all the mailing lists.

Install

See the TensorFlow install guide for thepip package, toenable GPU support, use aDocker container, andbuild from source.

To install the current release, which includes support forCUDA-enabled GPU cards (Ubuntu andWindows):

$ pip install tensorflow

A smaller CPU-only package is also available:

$ pip install tensorflow-cpu

To update TensorFlow to the latest version, add --upgrade flag to the abovecommands.

Nightly binaries are available for testing using thetf-nightly andtf-nightly-cpu packages on PyPi.

Try your first TensorFlow program

$ python

>>> import tensorflow as tf>>> tf.add(1, 2).numpy()3>>> hello = tf.constant('Hello, TensorFlow!')>>> hello.numpy()b'Hello, TensorFlow!'

For more examples, see theTensorFlow tutorials.

Contribution guidelines

If you want to contribute to TensorFlow, be sure to review thecontribution guidelines. This project adheres to TensorFlow'scode of conduct. By participating, you are expected touphold this code.

We use GitHub issues fortracking requests and bugs, please seeTensorFlow Discussfor general questions and discussion, and please direct specific questions toStack Overflow.

The TensorFlow project strives to abide by generally accepted best practices inopen-source software development:

Continuous build status

You can find more community-supported platforms and configurations in theTensorFlow SIG Build community builds table.

Official Builds

Build Type	Status	Artifacts
Linux CPU		PyPI
Linux GPU		PyPI
Linux XLA		TBA
macOS		PyPI
Windows CPU		PyPI
Windows GPU		PyPI
Android		Download
Raspberry Pi 0 and 1		Py3
Raspberry Pi 2 and 3		Py3
Libtensorflow MacOS CPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Linux CPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Linux GPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Windows CPU	Status Temporarily Unavailable	Nightly Binary Official GCS
Libtensorflow Windows GPU	Status Temporarily Unavailable	Nightly Binary Official GCS