hmm ok, but we are talking here about a 3x3 convolution with 3 input and 128 output channels. So less than 4000 parameters, compared to more than 10,000,000 of resnet50. For a similar operation it’s allocating twice the amount of memory, while the model only has 0.04% of the parameters?