Mistake in example code given in the MATLAB documentation for training multiple NN

In the documentation we are training 10 different neural networks, each initialized with different weights and biases. net is the variable for constructing the neural networks, x1 is the training dataset, t1 is the known labels used in training, x2 is the test dataset and t2 is the test label. Each neural network is stored in a cell variable NN{}.

After training, the evaluation is done using the test set t2 and x2, However, the mse calculation is done using mse(net, t2, y2)I think the correct statement should have been mse(NN{i}, t2, y2) since NN{} is the trained model and not net which is just a structure. Below is the code given in the link.

Should the function call be mse(NN{i}, t2, y2) instead of mse(net, t2, y2)?

net = feedforwardnet(10);
numNN = 10;
NN = cell(1, numNN);
perfs = zeros(1, numNN);
for i = 1:numNN
  fprintf('Training %d/%d\n', i, numNN);
  NN{i} = train(net, x1, t1);
  y2 = NN{i}(x2);
  perfs(i) = mse(net, t2, y2);
end

mse is a network performance function. It measures the network’s performance according to the mean of squared errors.

perf = mse(net,t,y,ew) takes these arguments:

• net Neural network
• t Matrix or cell array of targets
• y Matrix or cell array of outputs
• ew Error weights (optional)

As per the documentation of mse. So the first parameter should be a structure of the neural network type, with NN{i} being contained in y2 in that example, thus the matrix of outputs.