trainInputProvider.getProperties().setGroupByChannel(true);
trainInputProvider.getProperties().setScaleColors(true);
trainInputProvider.addInputModifier(new ScalingInputFunction(255));
// specify your own path
CIFAR10TestingInputProvider testInputProvider = new CIFAR10TestingInputProvider("cifar-10-batches-bin"); // specify your own path
testInputProvider.getProperties().setGroupByChannel(true);
testInputProvider.getProperties().setScaleColors(true);
testInputProvider.addInputModifier(new ScalingInputFunction(255));
BackPropagationTrainer<?> bpt = TrainerFactory.backPropagation(mlp, trainInputProvider, testInputProvider, new MultipleNeuronsOutputError(), new NNRandomInitializer(new RandomInitializerImpl(new Random(), -0.01f, 0.01f)), 0.02f, 0.5f, 0f, 0f, 0f, 1, 1000, 1);
bpt.addEventListener(new LogTrainingListener(Thread.currentThread().getStackTrace()[1].getMethodName(), false, true));