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Libraries & extensions

Explore libraries to build advanced models or methods using TensorFlow, and access domain-specific application packages that extend TensorFlow.


TensorFlow Probability is a library for probabilistic reasoning and statistical analysis.


Tensor2Tensor is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

TensorFlow Agents 

A library for reinforcement learning in TensorFlow.

TensorFlow Federated 

An open source framework for machine learning and other computations on decentralized data.

A Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy.

A language for distributed deep learning, capable of specifying a broad class of distributed tensor computations.


A research framework for fast prototyping of reinforcement learning algorithms.

TRFL (pronounced “truffle”) is a library for reinforcement learning building blocks created by DeepMind.


Makes it easy to store and manipulate data with non-uniform shape, including text (words, sentences, characters), and batches of variable length.

Unicode Ops 

Supports working with Unicode text directly in TensorFlow.

TensorFlow Ranking 

TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform.

Magenta is a research project exploring the role of machine learning in the process of creating art and music.


Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF.


A library from DeepMind for constructing neural networks.

Model Optimization 

The TensorFlow Model Optimization Toolkit is a suite of tools for optimizing ML models for deployment and execution.

TensorFlow Graphics 

Computer Graphics Meets Deep Learning.