Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch

• URL: http://arxiv.org/abs/2204.03418v1
• Date: Thu, 7 Apr 2022 13:03:09 GMT
• Title: Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch
• Authors: Lukas Hedegaard and Alexandros Iosifidis
• Abstract summary: Continual Inference is a Python library for implementing Continual Inference Networks (CINs) in PyTorch. We offer a comprehensive introduction to CINs and their implementation in practice, and provide best-practices and code examples for composing complex modules for modern Deep Learning.
• Score: 97.03321382630975
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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