A PyTorch implementation of MixNet architecture: MixNet: Mixed Depthwise Convolutional Kernels. Based on MobileNetV2, found by Neural Architecture Search, replacing depthwise convolution to the proposed mixed depthwise convolution (MDConv). Results: More accurate than previous models including MobileNetV2 (ImageNet top-1 accuracy +4.2%), ShuffleNetV2 (+3.5%), MnasNet (+1.3%), ProxylessNAS (+2.2%), and FBNet (+2.0%). MixNet-L achieves a new state-of-the-art 78.9% ImageNet top-1 accuracy under typical mobile settings (<600M FLOPS).
Slightly modified from MobileNetV3-PyTorch by Anjie Zheng.