When I use the alexnet to train the Cifar10, I use the following code to set the rand  seed:
random.seed(666)
np.random.seed(666)
torch.manual_seed(666)
torch.cuda.manual_seed_all(666)
torch.cuda.manual_seed(666)
torch.backends.cudnn.benchmark = True
torch.backends.cudnn.deterministic = True
And I train it twice, and print the input and loss every iter. But I find the loss of the two different running is different, however, the input is the same. Just as the content in red box.

image.png1440×637 661 KB

The code is the same, the input is the same, but why the computed loss is different?
Do someone know how it comes? Thank you very much!!