Yeah sure!
T_train = transforms.Compose([transforms.RandomHorizontalFlip(), transforms.RandomCrop(32, 4), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
But if the case was due to different random seeds, then one shouldn’t expect such drastic difference in accuracy. Moreover, the time taken during training for both is very different (it seems like the second method is always much faster regardless of what’s in T_train; also method 2’s performance get’s worse when you add in the random H-Flips and random crops).