Why don't we put models in .train() or .eval() modes in DCGAN example

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I understand that we need a stable running_mean and running_std for eval(). But I thought pytorch already keeps a running_mean and running_std during train() and use them for eval(). Is that not the case? I’m a bit confused on why we need to get a running_mean and running_std for eval() separately. We cannot use the running_mean and running_std from train()?

Also, I am using InstanceNorm2D which is suppose to perform the same in train() and eval()?

Thanks!