Documentation, -------------------, 
, TensorFlow is an end-to-end open source platform
for machine learning. It has a comprehensive, flexible ecosystem of
tools,
libraries, and
community 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 Python
and C++ APIs, as well as
non-guaranteed backward compatible API for
other languages.
Keep up-to-date with release announcements and security updates by subscribing
to
announce@tensorflow.org.
See all the mailing lists.
Install
See the TensorFlow install guide for the
pip package, to
enable GPU support, use a
Docker container, and
build from source.
To install the current release, which includes support for
CUDA-enabled GPU cards (Ubuntu and
Windows):
$ 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 above
commands.
Nightly binaries are available for testing using the
tf-nightly and
tf-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()
'Hello, TensorFlow!'
For more examples, see the
TensorFlow tutorials.
Contribution guidelines
If you want to contribute to TensorFlow, be sure to review the
contribution guidelines. This project adheres to TensorFlow's
code of conduct. By participating, you are expected to
uphold this code.
We use GitHub issues for
tracking requests and bugs, please see
TensorFlow Discuss
for general questions and discussion, and please direct specific questions to
Stack 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
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 Stable Release, 
, Release 1.15 / 2.x
Red Hat® Enterprise Linux® 7.6 CPU & GPU Python 2.7, 3.6, 
, 1.13.1 PyPI
Resources
Learn more about the
TensorFlow community and how to
contribute.
License
Apache License 2.0
