I have an imbalanced dataset, which has 3 classes. The major class has 10 times the size of the other 2 minority classes. Say the sizes of each class is [10000, 1000, 1000]. If I use the WeightedRandomSampler, the probability of the minority classes will be better than the major class, which means a batch from a loader will have the same numbers of each class. Does that mean that my dataloader will iterate more times than that of the imbalanced dataset? Suppose I have a batch size of 100, the imbalanced dataset will have 120 iterations((10000+1000+1000) / 100), and with the WeightedRandomSampler, the iteration will be 300?((10000+10000+10000) / 100). Is that correct?