Hi, my network is giving me different accuracies each time I’m running , before touching anything the difference was around 0.2 top1 scores.
Those are the elements I changed/added:
1.

torch.manual_seed(60)
torch.cuda.manual_seed(60)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
(There is no use in numpy so didn’t add a seed for numpy)

2.No Augmentations:

train_transform=transforms.Compose([
        #transforms.RandomHorizontalFlip(),
        #transforms.RandomCrop(32, 4),
        transforms.ToTensor(),
        normalize,
    ])



No data shuffle.
Saved the model initialization and loaded the same init for each run.

Now the difference is around 0.09.
What did I forget?  what other stochastic ingredients do we have?
Thanks.