I am trying to code a recurrent neural network (LSTM) to create music in python and was considering using multiple features instead of just the note pitch as an input into the network. Initially I had just the note pitch so it was fed into the network by one-hot encoding it. The other two features I want to add are the note duration and the offset between the notes. How should the input vector be organised so that all the data is fed through the network?
I have tried combining all of the data into a long vector with all 3 features one-hot encoded and then concatenated but this caused the output to become 'NaN'. Any help would be appreciated.
Link a gist of my code: