Calculate total number of parameters in pretrained models

calculate total number of parameters in pretrained models

calculate the total number of parameters in pretrained models
like alexnet,googlenet,...
clc;clear
%x=['googlenet','resnet18','resnet50','VGG16','darknet19','alexnet','mobilenet','Xception','custome'];
%par=[5976627,134272835,23487619,136310547,20838179,56880515,4233133,20808883,2985263]
%accuracy=[91.3,91.3,92,90.3,88.9,89.7,90.7,91.2,99.8]
%executiontime=[1,2,3,4,5,6,7,8,9]
%myDLnet=load('ALEXNET_1_among_5_folds.mat','netTransfer');%par 56880515
%myDLnet=load('xception_1_among_5_folds.mat','netTransfer');%par 20808883
%myDLnet=load('darknet19_1_among_5_folds.mat','netTransfer');%par 20838179
%myDLnet=load('googlenet_1_among_5_folds.mat','netTransfer');%par 5976627
%myDLnet=load('ResNet18_1_among_5_folds.mat','netTransfer');%par 11173251
%myDLnet=load('ResNet50_1_among_5_folds.mat','netTransfer');%par 23487619
%myDLnet=load('nasnetmobile_2_among_5_folds.mat','netTransfer');%par 4233133
% myDLnet=load('newcustomisedmodel_1_among_5_folds.mat','netTransfer');%par 2985263
% myDLnet=load('vgg16_1_among_5_folds.mat','netTransfer');%par 136310547
layers=myDLnet.netTransfer.Layers;
num_layers = size(layers,1);
num_para=0;
num_para1=0;
num_para2=0;
num_para3=0;
for i=2:num_layers
n=contains(class(myDLnet.netTransfer.Layers(i)),["Conv","Fully"]);
m=contains(class(myDLnet.netTransfer.Layers(i)),"Batch");
if (n==1)
num_para=num_para+prod(size(myDLnet.netTransfer.Layers(i,1).Weights));
num_para1=num_para1+prod(size(myDLnet.netTransfer.Layers(i,1).Bias));
end

if (m==1)
num_para2=num_para2+prod(size(myDLnet.netTransfer.Layers(i,1).Offset));
num_para3=num_para3+prod(size(myDLnet.netTransfer.Layers(i,1).Scale));
% disp(['num of Weights=',num2str(num_para),'for layer number =',num2str(i)])
% disp(['num of Bias=',num2str(num_para1),'for layer number =',num2str(i)])
end
end
total=num_para+num_para1;
disp(['total number of parameters=',num2str(total)])