FastONN -- Python based open-source GPU implementation for Operational Neural Networks

• URL: http://arxiv.org/abs/2006.02267v1
• Date: Wed, 3 Jun 2020 13:33:35 GMT
• Title: FastONN -- Python based open-source GPU implementation for Operational Neural Networks
• Authors: Junaid Malik, Serkan Kiranyaz and Moncef Gabbouj
• Abstract summary: This work introduces a fast GPU-enabled library for training operational neural networks, FastONN. FastONN is based on a novel vectorized formulation of the operational neurons. bundled auxiliary modules offer interfaces for performance tracking and checkpointing across different data partitions and customized metrics.
• Score: 25.838282412957675
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Operational Neural Networks (ONNs) have recently been proposed as a special class of artificial neural networks for grid structured data. They enable heterogenous non-linear operations to generalize the widely adopted convolution-based neuron model. This work introduces a fast GPU-enabled library for training operational neural networks, FastONN, which is based on a novel vectorized formulation of the operational neurons. Leveraging on automatic reverse-mode differentiation for backpropagation, FastONN enables increased flexibility with the incorporation of new operator sets and customized gradient flows. Additionally, bundled auxiliary modules offer interfaces for performance tracking and checkpointing across different data partitions and customized metrics.

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