Correct data augmentation with k-fold cross validation

I’m performing 10 k-fold cross validation on my neural network model. I’ve done the splits (k=10: 90% train, 10% validation), but It’s not clear for me if I should apply transforms (random horizontal flip, random rotation, etc) only on training set or both training and validation. What is the correct way to do it?