[](https://bestpractices.coreinfrastructure.org/projects/1486) [](https://securityscorecards.dev/viewer/?uri=github.com/tensorflow/tensorflow)
[](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:tensorflow)
[](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:tensorflow-py)
[](CODE_OF_CONDUCT.md)
Documentation |
|---|
 |
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of
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 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 provides stable Python and C++ APIs, as well as a
non-guaranteed backward compatible API for other languages.
Keep up-to-date with release announcements and security updates by subscribing to
[email protected]. See all the [mailing
lists](https://www.tensorflow.org/community/forums).
Install
See the TensorFlow install guide for the pip package, to [enable GPU
support](https://www.tensorflow.org/install/gpu), use a Docker container, and [build from
source](https://www.tensorflow.org/install/source).
To install the current release, which includes support for CUDA-enabled GPU cards (Ubuntu and Windows):
pip install tensorflow
Other devices (DirectX and MacOS-metal) are supported using Device Plugins.
A smaller CPU-only TensorFlow package is also available:
pip install tensorflow-cpu
To update TensorFlow to the latest version, add the --upgrade flag to the
commands above.
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()
b'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
Forum](https://discuss.tensorflow.org/) for general questions and discussion, and please direct specific questions to [Stack
Overflow](https://stackoverflow.com/questions/tagged/tensorflow).**
The TensorFlow project strives to abide by generally accepted best practices in open-source software development.
Patching guidelines
Follow these steps to patch a specific version of TensorFlow, for example, to apply fixes to bugs or security vulnerabilities:
- Clone the TensorFlow repository and switch to the appropriate branch for your desired version—for example,
r2.8for 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 the TensorFlow pip package from source.
Continuous build status
You can find more community-supported platforms and configurations in the TensorFlow 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
Resources
- TensorFlow.org * TensorFlow Tutorials * [TensorFlow Official
Models](https://github.com/tensorflow/models/tree/master/official) * TensorFlow Examples * [TensorFlow
Codelabs](https://codelabs.developers.google.com/?cat=TensorFlow) * TensorFlow Blog * [Learn ML with
TensorFlow](https://www.tensorflow.org/resources/learn-ml) * TensorFlow Twitter * [TensorFlow
YouTube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ) * [TensorFlow model optimization
roadmap](https://www.tensorflow.org/model_optimization/guide/roadmap) * TensorFlow White Papers * [TensorBoard
Visualization Toolkit](https://github.com/tensorflow/tensorboard) * TensorFlow Code Search
Learn more about the TensorFlow Community and how to Contribute.