tensorflow

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tensorflow

2019-12-05 |

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tensorflow

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

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

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

Keep up-to-date with release announcements and security updates by subscribing toannounce@tensorflow.org. 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 for CPU-only:

$ pip install tensorflow

Use the GPU package forCUDA-enabled GPU cards (Ubuntu and Windows):

$ pip install tensorflow-gpu

Nightly binaries are available for testing using thetf-nightly andtf-nightly-gpu 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()'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 to uphold this code.

We use GitHub issues for tracking 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 in open-source software development:

Continuous build status

Official Builds

Build Type	Status	Artifacts
Linux CPU		PyPI
Linux GPU		PyPI
Linux XLA		TBA
macOS		PyPI
Windows CPU		PyPI
Windows GPU		PyPI
Android
Raspberry Pi 0 and 1		Py2 Py3
Raspberry Pi 2 and 3		Py2 Py3

Community Supported Builds

Build Type	Status	Artifacts
Linux AMD ROCm GPU Nightly		Nightly
Linux AMD ROCm GPU Stable Release		Release 1.15 / 2.x
Linux s390x Nightly		Nightly
Linux s390x CPU Stable Release		Release
Linux ppc64le CPU Nightly		Nightly
Linux ppc64le CPU Stable Release		Release 1.15 / 2.x
Linux ppc64le GPU Nightly		Nightly
Linux ppc64le GPU Stable Release		Release 1.15 / 2.x
Linux CPU with Intel® MKL-DNN Nightly		Nightly
Linux CPU with Intel® MKL-DNN Supports Python 2.7, 3.4, 3.5, 3.6 and 3.7		1.14.0 PyPI
Red Hat® Enterprise Linux® 7.6 CPU & GPU Python 2.7, 3.6		1.13.1 PyPI