Hi, thanks for your great work on sharing the one and only working keras-based implementation of deep learning models for NLP that can be found on the web.
Suppose I want to move on to something original by adding one or more channels to the input data,which may be a color channel in image or another language, can you suggest which parts of your code I should look into and share with me any of your ideas on the actual changes needed?
I have had a lot of pains before with getting dimensions of layers matching and doing away with the unused output warning. I would be extremely grateful if you can offer any help.
Hi, thanks for your great work on sharing the one and only working keras-based implementation of deep learning models for NLP that can be found on the web.
Suppose I want to move on to something original by adding one or more channels to the input data,which may be a color channel in image or another language, can you suggest which parts of your code I should look into and share with me any of your ideas on the actual changes needed?
I have had a lot of pains before with getting dimensions of layers matching and doing away with the unused output warning. I would be extremely grateful if you can offer any help.