|author||Orion Hodson <email@example.com>||Sat Apr 11 20:59:29 2020 +0100|
|committer||Orion Hodson <firstname.lastname@example.org>||Mon Apr 13 12:06:33 2020 +0100|
Add explicit dependency on jni_headers Preparation for removing implicit include paths for jni.h from soong. Bug: 152482542 Test: m checkbuild Change-Id: Ic668711aceb3a5bb59b89169977d8e2b565b391a
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.
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.
>>> import tensorflow as tf >>> tf.add(1, 2).numpy() 3 >>> hello = tf.constant('Hello, TensorFlow!') >>> hello.numpy() '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:
|Raspberry Pi 0 and 1||Py2 Py3|
|Raspberry Pi 2 and 3||Py2 Py3|
|Linux AMD ROCm GPU Nightly||Nightly|
|Linux AMD ROCm GPU Stable Release||Release 1.15 / 2.x|
|Linux s390x Nightly||Nightly|
|Linux s390x CPU Stable Release||Release|
|Linux ppc64le CPU Nightly||Nightly|
|Linux ppc64le CPU Stable Release||Release 1.15 / 2.x|
|Linux ppc64le GPU Nightly||Nightly|
|Linux ppc64le GPU Stable Release||Release 1.15 / 2.x|
|Linux CPU with Intel® MKL-DNN Nightly||Nightly|
|Linux CPU with Intel® MKL-DNN Stable Release||Release 1.15 / 2.x|
|Red Hat® Enterprise Linux® 7.6 CPU & GPU |
Python 2.7, 3.6