commit | bda2e777585dfdd8811d463523bf2efa17a6ac87 | [log] [tgz] |
---|---|---|
author | Justin Lebar <jlebar@google.com> | Tue May 18 22:05:50 2021 -0700 |
committer | TensorFlower Gardener <gardener@tensorflow.org> | Wed May 19 10:15:11 2021 -0700 |
tree | 019a19e02a48b2035ded85d2ced56ff2e7d7c626 | |
parent | 4a51bad97eeb3c371b3c4813b850b65910db94da [diff] |
Support int8x4 fused convolutions on XLA:GPU. - Add a new custom-call builder in xla_builder that accepts a Window and ConvolutionDimensionNumbers. This is necessary to allow external clients to create an appropriate custom-call. - Fix buffer_comparator's handling of int8x4 outputs. I'm not sure how this ever worked, even for int8x1. If you asked it to read N values, it would read N int32s. For int8x1, I don't see where we divide by 4. Anyway the new implementation is simpler and works for int8x1 and intx8x4. - Small fixes to StreamExecutor and various parts of XLA to make int8x4 work. Not done in this CL: - Support int8x32 convolutions. PiperOrigin-RevId: 374571517 Change-Id: Ib8fc7f53c4ec3b894f34f944aeaeeef2006a7576
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.
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
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:
Build Type | Status | Artifacts |
---|---|---|
Linux CPU | PyPI | |
Linux GPU | PyPI | |
Linux XLA | TBA | |
macOS | PyPI | |
Windows CPU | PyPI | |
Windows GPU | PyPI | |
Android | ||
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 |
See TensorFlow SIG Build to find our list of community-supported TensorFlow builds.
Learn more about the TensorFlow community and how to contribute.