I understand that after training a model with dropout layers, you set it to net.eval() for inference.
But I thought there should be a way to apply the learned weights (that is, the checkpoint) from the training to another model which is identical to the original trained model, but without the dropout layers.
If anyone let me know, I would appreciate that.