Hi,
Sorry if this is a lame question.
But what happens to the forward pass value when we do a validation forward pass?
To elaborate my question, because we need the forward pass value when updating the weights, and we only make gradients zero (before the optimizer.step()), can validation forward pass value mess up with the weight update? or the model parameters only remember the last forward pass value so the validation forward pass is forgotten when we do the update (because we do the train forward pass later)?