How to run neural network with dividing data to 2sets instead of 3 sets ?

I know that in R software (neuralnet package) the datasets divides to two set of training and test sets I was wondering if there is a possibility to run the neural network with two sets of data similar to neuralnet?I would appreciate if someone could correct this script of applying ANN with two sets of data....Thanks

% if I have trainX and trainY as trainSet data and testX and testY as
% testSet.AS I want to train the model with trainSet and test the model with the
%testSet
inputs = trainX';
targets = trainY';

net = newfit(trainX(:,ind)', trainY', 17);
    net.performFcn = 'mse';
    net = train(net, trainX(:,ind)', trainY');

hiddenLayerSize = 5;
for i = 1:30 % to repeat for 30 times with different initial weights
    net = fitnet(hiddenLayerSize);
    net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
    net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
    net.trainFcn = 'trainlm'; 
    net.performFcn = 'mse';
   [net,tr] = train(net,trainX',trainY');

      outputs = net(testX');
      errors = gsubtract(testY',outputs);

      performance = perform(net,testY',outputs);% Iam not sure if it is correct

      save(net)
  end

[Rita]

Thanks Walter,I have copied my script would you mind correcting this?Thanks

Answer 1

[Walter Roberson]

https://www.mathworks.com/help/nnet/ref/dividerand.html and give 0 as the validation ratio.

[Walter Roberson]

Before the train() call,

trainfrac = 0.8;

net.divideParam.trainRatio = trainfrac;
net.divideParam.valRatio = 0;
net.divideParam.testRatio = 1-trainfrac;