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.
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
>>> 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.
The TensorFlow project strives to abide by generally accepted best practices in open-source software development.
Follow these steps to patch a specific version of TensorFlow, for example, to apply fixes to bugs or security vulnerabilities:
r2.8for version 2.8.
You can find more community-supported platforms and configurations in the TensorFlow SIG Build community builds table.
|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|