I have an autoencoder deep network, and I notice that when I use  nn.Sequential , the generalization performance is better than when I don’t use it (i.e. explicitly pass the inputs through layers). Has anyone else noticed this behavior, or can provide an explanation as to why this is? Does Pytorch handle regularization differently in a sequential block?