---
id: tensorflow-addons
version: "0.23.0"
license: Apache 2.0
license_treatment: permissive
maintenance: dormant
---

# tensorflow-addons — TensorFlow Addons.

License: permissive · Maintenance: dormant · Downloads: 1.0M/mo

## 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 above — verify before relying.

TensorFlow Addons provides experimental operators, layers, metrics, losses, and optimizers that extend core TensorFlow with functionality not yet ready for the main library.

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

pip install tensorflow-addons
uv add tensorflow-addons
poetry add tensorflow-addons

## Installing tensorflow-addons

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.

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

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).

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

- License: Apache 2.0 (permissive)
- Python support: unspecified
- Install friction: medium
- Maintenance: dormant
- Downloads: 1.0M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

tensorflow extensions, custom tensorflow layers, tensorflow experimental operators, machine learning addons, tensorflow metrics losses, deep learning utilities, tensorflow-extension, experimental-ml

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