Clone this repo:
  1. b481ac8 Merge pull request #27048 from willbattel:patch-1 by TensorFlower Gardener · 2 hours ago master
  2. 152095e Add gemmlowp-threadpool multithreading to the depthwiseconv implementation for the quantized path. by Lu Wang · 8 hours ago
  3. 36f817a compat: Update forward compatibility horizon to 2019-03-23 by A. Unique TensorFlower · 16 hours ago
  4. 840022b Support 0-D ITensors in TF-TRT. This is required to import #25624 which adds CombinedNonBatchSuppression support. by Guangda Lai · 18 hours ago
  5. 1e4725c Automated rollback of commit 359e8c791c73ff366797c6a3ed1861e9af05697c by Randy Dodgen · 20 hours ago

Documentation
Documentation

TensorFlow is an open source software library for numerical computation using data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit.

TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization for the purposes of conducting 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 backwards compatible API's for C++, Go, Java, JavaScript and Swift.

Keep up to date with release announcements and security updates by subscribing to announce@tensorflow.org.

Installation

To install the current release for CPU-only:

pip install tensorflow

Use the GPU package for CUDA-enabled GPU cards:

pip install tensorflow-gpu

See Installing TensorFlow for detailed instructions, and how to build from source.

People who are a little more adventurous can also try our nightly binaries:

Nightly pip packages

  • We are pleased to announce that TensorFlow now offers nightly pip packages under the tf-nightly and tf-nightly-gpu project on pypi. Simply run pip install tf-nightly or pip install tf-nightly-gpu in a clean environment to install the nightly TensorFlow build. We support CPU and GPU packages on Linux, Mac, and Windows.

Try your first TensorFlow program

$ python
>>> import tensorflow as tf
>>> tf.enable_eager_execution()
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
'Hello, TensorFlow!'

Learn more examples about how to do specific tasks in TensorFlow at the tutorials page of tensorflow.org.

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, so 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

Continuous build status

Official Builds

Build TypeStatusArtifacts
Linux CPUStatuspypi
Linux GPUStatuspypi
Linux XLAStatusTBA
MacOSStatuspypi
Windows CPUStatuspypi
Windows GPUStatuspypi
AndroidStatusDownload
Raspberry Pi 0 and 1Status StatusPy2 Py3
Raspberry Pi 2 and 3Status StatusPy2 Py3

Community Supported Builds

Build TypeStatusArtifacts
IBM s390xBuild StatusTBA
Linux ppc64le CPU NightlyBuild StatusNightly
Linux ppc64le CPU Stable ReleaseBuild StatusRelease
Linux ppc64le GPU NightlyBuild StatusNightly
Linux ppc64le GPU Stable ReleaseBuild StatusRelease
Linux CPU with Intel® MKL-DNN NightlyBuild StatusNightly
Linux CPU with Intel® MKL-DNN
Supports Python 2.7, 3.4, 3.5 and 3.6
Build Status1.13.1 pypi

For more information

Learn more about the TensorFlow community at the community page of tensorflow.org for a few ways to participate.

License

Apache License 2.0