I’m using Google’s EfficientNet (the small version) on an RTX 3090. I’ve found that overall epoch time doesn’t vary much whether I train with big batches or small batches. Similarly, with classification I’m not seeing much difference in images/second whether I use big or small batches.
Am I missing something? I thought the idea of a batch was that all of the images got processed in parallel, so batch processing time should be relatively constant whether it’s 1 image or 32.