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burgerkingeater/tensorflow

An Open Source Machine Learning Framework for Everyone

Documentation
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 for CPU-only:

$ pip install tensorflow

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

$ pip install tensorflow-gpu

Nightly binaries are available for testing using the
tf-nightly and
tf-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 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:

CII Best Practices
Contributor Covenant

Continuous build status

Official Builds

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

Community Supported Builds

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

Resources

Learn more about the
TensorFlow community and how to
contribute.

License

Apache License 2.0

Languages

C++60.5%Python30.6%HTML3.7%Go1.3%MLIR1.0%Java0.8%C0.6%Shell0.5%Jupyter Notebook0.4%Objective-C++0.2%Objective-C0.1%Dockerfile0.1%Swift0.0%Makefile0.0%Batchfile0.0%Smarty0.0%PHP0.0%Pawn0.0%C#0.0%Perl0.0%Ruby0.0%CMake0.0%LLVM0.0%Assembly0.0%Pascal0.0%RobotFramework0.0%
Apache License 2.0
Created November 22, 2019
Updated November 22, 2019