Is there a way to increase the number of units in a dense layer and still be able to load previously saved weights that used a lower number of units?
In theory you could add more units and initialize them randomly, but that would make the original training worthless. A more common method for increasing the complexity of a model while leveraging earlier training is to add more layers and resume training.
I am starting to learn how to build neural networks. Here is what I did:
I ran a number of epochs with units in my dense layer at 512.
Then I saved the weights with the best accuracy. 
Then I increased the number of units in my dense layer to 1024 and attempted to reload my weights with the best accuracy but with the old weights of 512. 
I got an error. I understand why I got the error but I am wondering if there is a way to increase the number of units and still be able to use my saved weights or do I need to retrain my model from the beginning again?