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Documentation |
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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.
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
Other devices (DirectX and MacOS-metal) are supported using
Device plugins.
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.
$ 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.
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.
You can find more community-supported platforms and configurations in the
TensorFlow SIG Build community builds table.
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 |
Learn more about the
TensorFlow community and how to
contribute.
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Dear OpenI User
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