I timed the training loops myself (using the resnet example):
Train Epoch: 1 [7341/29371 (24.9940 %)]         Loss: 4.6176743507385254        GPU Time: 0:08:22.217366        Dataloader Time: 0:01:01.206019    Others: 0:00:11.105754
Train Epoch: 1 [14683/29371 (49.9915 %)]        Loss: 3.3774175643920898        GPU Time: 0:08:11.256317        Dataloader Time: 0:00:43.877545    Others: 0:00:09.344856
Train Epoch: 1 [22025/29371 (74.9889 %)]        Loss: 3.6628768444061279        GPU Time: 0:08:09.219690        Dataloader Time: 0:00:41.986479    Others: 0:00:08.147579
Train Epoch: 1 [29367/29371 (99.9864 %)]        Loss: 2.7599744796752930        GPU Time: 0:08:24.159365        Dataloader Time: 0:00:40.122311    Others: 0:00:09.004757

This is the total time over 1/4 of the total datasets.