Bug: 69264167

Clone this repo:
  1. 3366973 Merge remote-tracking branch 'aosp/upstream-master' into rebase_tf by Miao Wang · 2 weeks ago master
  2. d44ca8d Merge remote-tracking branch 'aosp/upstream-master' into rebase_tf by Miao Wang · 4 weeks ago
  3. bb52a66 ConfigProto.experimental.num_dev_to_dev_copy_streams defaults to 0 by A. Unique TensorFlower · 4 weeks ago
  4. 4cca48f Allow eval_metrics to be None in TPUEstimatorSpec by Yanan Cao · 4 weeks ago
  5. 0272513 - Use InlinedVector for ShapeIndex. by Yunxing Dai · 4 weeks ago


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.

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


See Installing TensorFlow for instructions on how to install our release binaries or 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
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> sess.run(hello)
'Hello, TensorFlow!'
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> sess.run(a + b)
>>> sess.close()

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
Windows CPUStatuspypi
Windows GPUStatuspypi
AndroidStatusDownload demo APK, native libs build history

Community Supported Builds

Build TypeStatusArtifacts
IBM s390xBuild StatusTBA
IBM ppc64le CPUBuild StatusTBA
IBM ppc64le GPUBuild StatusTBA
Linux CPU with Intel® MKL-DNN®Build StatusTBA

For more information

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


Apache License 2.0