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danieldjohnson / biaxial-rnn-music-composition

A recurrent neural network designed to generate classical music.
BSD 2-Clause "Simplified" License
1.92k stars 379 forks source link

doesn't work, need help #32

Open Casski opened 7 years ago

Casski commented 7 years ago

everytime i've tried it we got this :
musicbots@music:~/biaxial-rnn-music-composition$ python main.py Loaded bwv798 Loaded bwv783 Loaded bwv781 Loaded bwv796 Loaded bwv797 Loaded bwv800 Loaded bwv789 Loaded bwv776 Loaded bwv784 Loaded bwv779 Loaded bwv793 Loaded bwv792 Loaded bwv794 Loaded bwv795 Loaded bwv782 Loaded bwv788 Loaded bwv772 Loaded bwv775 Loaded bwv791 Loaded bwv801 Loaded bwv774 Loaded bwv787 Loaded bwv780 Loaded bwv786 Loaded bwv790 Loaded bwv778 Loaded bwv777 Loaded bwv799 Loaded bwv785 Loaded bwv773 /home/musicbots/biaxial-rnn-music-composition/model.py:370: UserWarning: Updatin g an OrderedUpdates with a non-ordered dictionary with 2+ elements could make your code non-deterministic self.walk_input: next_input /home/musicbots/biaxial-rnn-music-composition/model.py:373: UserWarning: Updatin g an OrderedUpdates with a non-ordered dictionary with 2+ elements could make your code non-deterministic updates.update({hidden:newstate for hidden, newstate, layer in zip(self.walk_h iddens, new_states, self.time_model.layers) if has_hidden(layer)}) Killed

we tried it on multiple machines, as well as digital ocean always comes back to this, can anyone help me getting this to work? i would really like it to see it working

jzuern commented 6 years ago

Try to decrease the size of the model (number of neurons per layer) m = model.Model([100,00],[100,50], dropout=0.5) worked for me, while with m = model.Model([300,00],[100,50], dropout=0.5) I got the same error as you.