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tensorflow-addons

TensorFlow Addons.

With conditionsPyPI LibrariesReleased Nov 20231.0M downloads / moApache 2.0Platform wheel

Decision gist · record as of 2026-08-14

platform wheels — tensorflow_addons-0.23.0-cp310-cp310-macosx_10_14_x86_64.whl · tensorflow_addons-0.23.0-cp310-cp310-macosx_11_0_arm64.whl · tensorflow_addons-0.23.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
v0.23.0 · released 2023-11-28 · 2 runtime deps: packaging, typeguard

Yes-with-conditions. TensorFlow Addons is worth installing if you need specific experimental components that were stable in the 0.23.0 release and your TensorFlow version is compatible. However, the dormant status (no releases in 990 days) means you should verify compatibility with your current TensorFlow and Python versions before committing. Do not use this package for new projects expecting ongoing maintenance or security updates.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires TensorFlow to be installed separately; wheels are pre-built for Python 3.9, 3.10, 3.11 on x86_64 Linux and macOS (Intel and ARM).
  • Medium install friction due to compiled wheels for specific Python versions and platforms.
  • Package is dormant—last release was 990 days ago—so expect no active maintenance or bug fixes.

License · maintenance · safety

Apache 2.0 (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions, requiring only license and copyright notice retention.

last release 2023-11-28 (990 days)

0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,030,500 downloads/mo, #4,472 on PyPI

Verify before relying

pip install tensorflow-addons==0.23.0
import tensorflow_addons as tfa
import packaging
import typeguard
  • Whether tensorflow-addons 0.23.0 is compatible with recent TensorFlow versions (fact sheet does not specify TensorFlow version constraint).
  • Whether dormant status means the package will work with current Python and TensorFlow ecosystem or if breaking changes have accumulated.
  • What specific operators, layers, metrics, losses, and optimizers are included in 0.23.0.
Same gist for agents: .md · .json

What it is and what it does

TensorFlow Addons is a collection of experimental machine learning components—custom layers, loss functions, metrics, and optimizers—that extend TensorFlow but are not yet part of the core library. These additions target either emerging techniques whose broad applicability is still unclear or specialized functionality used by smaller subsets of the ML community. The package acts as an incubator for ideas that may eventually graduate to core TensorFlow or remain as optional extensions.

The package depends on packaging and typeguard for runtime support. It is distributed as pre-compiled wheels for Python 3.9, 3.10, and 3.11 on Linux x86_64 and macOS (both Intel and ARM). However, the package has been dormant for nearly three years—the last release was in November 2023—meaning no active maintenance, bug fixes, or compatibility updates are expected. This makes it risky for new projects or those requiring ongoing support.

Use it for

  • Experimenting with novel layer architectures or optimization algorithms not yet available in core TensorFlow.
  • Implementing specialized loss functions or metrics for niche machine learning domains.
  • Prototyping research ideas before deciding whether to contribute them upstream to TensorFlow.
  • Using well-tested experimental components in production if they were stable at the time of the last release.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes-with-conditions.

TensorFlow Addons is worth installing if you need specific experimental components that were stable in the 0.23.0 release and your TensorFlow version is compatible. However, the dormant status (no releases in 990 days) means you should verify compatibility with your current TensorFlow and Python versions before committing. Do not use this package for new projects expecting ongoing maintenance or security updates.

Install

tensorflow-addons on PyPI

Before you install

Medium install friction due to compiled wheels for specific Python versions and platforms. Package is dormant—last release was 990 days ago—so expect no active maintenance or bug fixes.

Requires TensorFlow to be installed separately; wheels are pre-built for Python 3.9, 3.10, 3.11 on x86_64 Linux and macOS (Intel and ARM).

License in practice

Apache 2.0 permissive license allows commercial and private use with minimal restrictions, requiring only license and copyright notice retention.

Quickstart

pip install tensorflow-addons==0.23.0
import tensorflow_addons as tfa
import packaging
import typeguard

Verify before relying

  • Whether tensorflow-addons 0.23.0 is compatible with recent TensorFlow versions (fact sheet does not specify TensorFlow version constraint).
  • Whether dormant status means the package will work with current Python and TensorFlow ecosystem or if breaking changes have accumulated.
  • What specific operators, layers, metrics, losses, and optimizers are included in 0.23.0.

Package facts

LicenseApache 2.0 permissive
Python supportNot specified
Install frictionMedium. Platform-specific wheel
Runtime dependencies
2 packages
packagingtypeguard
MaintenanceDormant 990 days since the last release
First released
Downloads1,030,500 / month, #4,472 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: MathematicsTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules

Evidence: tensorflow_addons-0.23.0-cp310-cp310-macosx_10_14_x86_64.whl; tensorflow_addons-0.23.0-cp310-cp310-macosx_11_0_arm64.whl; tensorflow_addons-0.23.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; tensorflow_addons-0.23.0-cp311-cp311-macosx_10_14_x86_64.whl; tensorflow_addons-0.23.0-cp311-cp311-macosx_11_0_arm64.whl; tensorflow_addons-0.23.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; tensorflow_addons-0.23.0-cp39-cp39-macosx_10_14_x86_64.whl; tensorflow_addons-0.23.0-cp39-cp39-macosx_11_0_arm64.whl; tensorflow_addons-0.23.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Tags

Capabilities
tensorflow extensionscustom tensorflow layerstensorflow experimental operatorsmachine learning addonstensorflow metrics lossesdeep learning utilities
Topics
tensorflow-extensionexperimental-ml
PyPI keywords
tensorflowaddonsmachinelearning

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See also tf-keras-nightly · tf-keras · tf-slim · Keras-Preprocessing · keras-nightly · tensorflow-metadata · keras · tensorflow-probability · tensorflow-graphics · tfp-nightly