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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?
The text was updated successfully, but these errors were encountered:
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?
The text was updated successfully, but these errors were encountered: