When you train deep learning model with SGD, batch composes of randomly selected data or sequentially selected data as a default.
I want to compare between uniform class batch training and not uniform class batch training.
More specifically, for CIFAR-10 task, when batch size = 10, each batch has 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 labeled data. Otherwise, Not uniform class batch training means that each batch has 0, 0, 0, 2, 4, 5, 5, 7, 8, 9. You don’t care the order of labels.