|Linux Py2 CPU|
|Linux Py3 CPU|
|Linux Py2 GPU|
|Linux Py3 GPU|
TensorFlow Addons is a repository of contributions that conform to well-established API patterns, but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. However, in a fast moving field like ML, there are many interesting new developments that cannot be integrated into core TensorFlow (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the community).
Standardized API within Subpackages
User experience and project maintainability are core concepts in TF-Addons. In order to achieve these we require that our additions conform to established API patterns seen in core TensorFlow.
Periodic Evaluation of Subpackages
Based on the nature of this repository, there will be contributions that in time become dated and unused. In order to keep the project maintainable, SIG-Addons will perform periodic reviews and deprecate contributions which will be slated for removal. More information will be available after we submit a formal request for comment.
for end-to-end examples of various addons.
To install the latest version, run the following:
pip install tensorflow-addons
Note: You will also need TensorFlow 2.0 or higher.
To use addons:
import tensorflow as tf import tensorflow_addons as tfa
Installing from Source
You can also install from source. This requires the Bazel build system.
git clone https://github.com/tensorflow/addons.git cd addons # This script links project with TensorFlow dependency ./configure.sh bazel build build_pip_pkg bazel-bin/build_pip_pkg artifacts pip install artifacts/tensorflow_addons-*.whl
TF-Addons is a community led open source project. As such, the project depends on public contributions, bug-fixes, and documentation. Please see contribution guidelines for a guide on how to contribute. This project adheres to TensorFlow's code of conduct. By participating, you are expected to uphold this code.
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