# Should you reshuffle your dataset after you use five or ten crop data augmentation in general machine learning?

My data was shuffled randomly first then I applied a five crop data augmentation. Now my batch went from [8, 3, 256, 256] to [40, 3, 256, 256] as you can see each 256x256 3 channel images were split into 5 crops increasing the total size to 40. I also double checked the array for ordering and the new cropped images are in order form so I had to do the same thing for my labels. A one-hot encoding example would be [1,1,1,1,1, 0,0,0,0,0, 1,1,1,1,1 ... 1,1,1,1,1]. Right now my labels is a [40, 1] vector. My current concern is should I reshuffle my images again? The neural network should recognize each image as an individual image but I am not confident about the effect of the paired ordering labels.