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sonnet

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1,310
Python

Project Description

TensorFlow-based neural network library

sonnet: TensorFlow-based neural network library

Project Title

sonnet — TensorFlow-based Neural Network Library for Machine Learning Research

Overview

Sonnet is a neural network library built on top of TensorFlow 2, designed to provide simple, composable abstractions for machine learning research. Developed by DeepMind, it offers a flexible programming model centered around the snt.Module concept, allowing users to construct neural networks for various purposes with ease.

Key Features

  • Flexible and composable abstractions for building neural networks
  • Built on top of TensorFlow 2, leveraging its capabilities
  • Designed for un/supervised learning, reinforcement learning, and more
  • Predefined modules and networks for common tasks (e.g., snt.Linear, snt.Conv2D, snt.nets.MLP)

Use Cases

  • Researchers and developers building neural networks for machine learning tasks
  • Users requiring a flexible and customizable framework for their ML models
  • Projects involving un/supervised learning, reinforcement learning, and other advanced ML techniques

Advantages

  • Simple and powerful programming model centered around snt.Module
  • Highly customizable and unopinionated, allowing users to build their own modules and training frameworks
  • Clear and focused codebase, with defaults and choices explained

Limitations / Considerations

  • Lacks a built-in training framework, requiring users to build or adopt their own
  • May require more setup and configuration compared to more opinionated frameworks

Similar / Related Projects

  • TensorFlow: A comprehensive open-source machine learning framework that Sonnet is built on top of.
  • PyTorch: Another popular open-source ML framework, known for its dynamic computation graph and ease of use.
  • Keras: A high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.

Basic Information


📊 Project Information

🏷️ Project Topics

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📚 Documentation


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Project Information

Created on 4/3/2017
Updated on 11/23/2025