| commit | 99a7bc967d27f9d2acf1268cf35a2412d506f5b2 | [log] [tgz] |
|---|---|---|
| author | Niklas Vangerow <nikv@google.com> | Fri Oct 03 16:53:50 2025 |
| committer | TensorFlower Gardener <gardener@tensorflow.org> | Fri Oct 03 17:01:53 2025 |
| tree | 88c1b9036083ec091df5365416cf9a03a75ed404 | |
| parent | d05adb4d7350f3e4786ae711eb582ce76c579b8d [diff] |
BufferValue::SizeFunction should be AnyInvocable SizeFunction is often passed around with std::move, but rarely if ever can it actally be 'moved'. We can't use move captures with the old definition of SizeFunction and therefore have to use clever workarounds for lifetime issues with reference captures. This patch aims to change this once and for all. While the size function can still be passed around by reference/pointer, we explicitly forbid copies to allow real moves. PiperOrigin-RevId: 814730267
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 within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the framework is versatile enough to be used in other areas as well.
TensorFlow provides stable Python and C++ APIs, as well as a 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!'
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Follow these steps to patch a specific version of TensorFlow, for example, to apply fixes to bugs or security vulnerabilities:
r2.8 for version 2.8.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.