The Dynamic Neural Network Toolkit

Dynamic Computational Graph

DyNet builds its computational graph on the fly. This makes variable-input and variable-output models simple to implement with high performance.

Dynamic Operation Batching

DyNet automatically reorganizes operations into batches for maximum performance, without requiring the developer to do so.

Ideal for Complex Structures

DyNet is well-suited for natural language processing, graph structures, reinforcement learning, and other complex state spaces.

Get Started

Tutorials

Learn how to use DyNet

Examples

Browse projects built using DyNet

Companies & Universities supporting DyNet

Carnegie Mellon University
Bar-Ilan University
Petuum
Allen Institute for Artificial Intelligence
Nara Institute of Science and Technology
University of Washington
Unbabel