How can i configure the dataloader to accept a batch size that is larger than the dataset size? Is it possible for the dataloader to continue sampling from the dataset?
uti_va_loader = torch.utils.data.DataLoader(uti_va_data, 
                                            batch_size=args.batch_size, 
                                            shuffle=True, 
                                            num_workers=0, 
                                            drop_last=False,
                                            pin_memory=torch.cuda.is_available())

This line is completely skipped if the batch size is larger than the dataset size.
for batch_idx, data in enumerate(uti_va_loader): 
    print(data.size())