I notice that in Trainer.train() self.save_model() is called at certain times to save all of the shared weights in the "super graph" (my terminology), but I don't see that the best dag is tracked such that at the end of train() we have the best DAG/model RNN for the PTB task. save_model() saves all of the weights for the entire shared weight space, but doesn't show which DAG (which sub-graph of the larger graph) represents the best RNN constructed during training - unless I'm missing something?
I notice that in Trainer.train() self.save_model() is called at certain times to save all of the shared weights in the "super graph" (my terminology), but I don't see that the best dag is tracked such that at the end of train() we have the best DAG/model RNN for the PTB task. save_model() saves all of the weights for the entire shared weight space, but doesn't show which DAG (which sub-graph of the larger graph) represents the best RNN constructed during training - unless I'm missing something?