Hello,

I noticed that EdgeImpulse has two MobileNetV2 architecture settings, the one with weights for alpha 0.1 and for alpha 0.35. However in the documentation it is stated that it is possible to get the models with alpha 0.05 aswell. It is stated in FOMO documentation that the smallest version of FOMO (96x96 grayscale input, MobileNetV2 0.05 alpha) runs in <100KB RAM, however when I try to set the alpha in expert mode to 0.05 and train the model, I get the exact same inference time, peak ram usage and flash usage as with alpha 0.1. Did I set the alpha incorrectly? The weights I used are from MobileNetV2 arcitecture:

WEIGHTS_PATH = ‘./transfer-learning-weights/edgeimpulse/MobileNetV2.0_05.96x96.grayscale.bsize_64.lr_0_05.epoch_334.val_loss_4.53.hdf5’

Thank you in advance!