Solved by AladdinPerzon in post #2 
              
              
                In PyTorch (and TensorFlow for that matter) how data augmentation works is that it’s done on the fly as part of image preprocessing (and preferably run in parallel on the CPU while the model is training on the GPU). This means that you do not need to run any augmentation and then store on disk, actu…