I am well aware that a model can be set to train or eval mode and that layers like dropout and batchnorm behave differently depending on this switch.
Recently, however, I have seen repos where they train a model(resnet152 to be specific) in eval mode - i.e the model is set to eval and then trained. Is it legit to do this(they also get sota results for their domain of interest)? if yes, in what situations would one take this approach?