Limit_train_batches vs val_check_interval
Does limit_train_batches=0.5 and val_check_interval=0.5 effectively do the same thing (minus impacting the total number of epochs)? That is, if my data loader is shuffling and I use limit_train_batches, can I safely assume that after 2 epochs I will have gone through the whole dataset or will I only go through the same 50% of the training data twice? The docs are not super clear on this point and this issue is a bit confusing as to what is going on: #2928
Also, is this statement true or false depending on single GPU vs DDP?
Thank you!