BMXNet 2: An Open Source Framework for Low-bit Networks - Reproducing, Understanding, Designing and Showcasing
Joseph Bethge, Christian Bartz, Haojin Yang, Christoph Meinel · 2020
Binary and quantized neural networks are a promising technique to run convolutional neural networks on mobile or embedded devices. BMXNet 2 is an open-source framework that provides a broad basis for academia and industry. It provides a modern implementation of binary and quantized layers with a wide array of implemented state-of-the-art models. Our implementation fosters reproducibility of other works and our own work through publishing model code, hyperparameters, detailed model graphs, and training logs. Furthermore, we implement several applications for BNNs, including demo applications, which can run on a smartphone or a Raspberry Pi. The code can be found online: https://github.com/hpi-xnor/BMXNet-v2