Papers › Continual Inference: A Library for Efficient Online Inference with Deep Neural...
Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch
Lukas Hedegaard, Alexandros Iosifidis
We present Continual Inference, a Python library for implementing Continual Inference Networks (CINs) in PyTorch, a class of Neural Networks designed specifically for efficient inference in both online and batch processing scenarios. We offer a comprehensive introduction and guide to CINs and their implementation in practice, and provide best-practices and code examples for composing complex modules for modern Deep Learning. Continual Inference is readily downloadable via the Python Package Index and at \url{www.github.com/lukashedegaard/continual-inference}.
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