you apply some sort of transformation you have a transformation function the apply to your input data and in data augmentation there's always this trade-off of diversity and validity that's being managed so so yeah you want to create novel and realistic training samples without augmenting them so much that you change their underlying inherent label so diversity it means growing the the reach of your data set or making your data set more broad and validity is making sure that you're not blowing up your samples so much that