

The last convolution block expands the output of the last InvertedResidual block by a factor of 6. The implementation is aligned with the Large and Small configurations described on the paper and can adapt to different values of the multiplier parameter.


Similarly to other models such as MobileNetV2, a dropout layer is placed just before the final Linear layer of the classifier.


The InvertedResidual class is the main building block of the network. Here are some notable implementation details of the block along with its visualization which comes from Figure 4 of the paper: