Hello everyone,
I found a phenomenon when training a network model. When the iteration of dataset is finished in a epoch, the DataLoader spends about 10s before re-iterating the dataset for the next epoch. This may mean a lot for some models trained on small dataset.
I defined a lot of data augmentation method in the initialization of Dateset, and I set pin_memory to be True, using 8 num_workers.
I did a simple experiment to measure the time needed for initializing Dataset and DataLoader, but the mean time is just about 0.1~0.15s.
Do you have any idea about this question? Thank you.