I posted this in the other thread. You can use this:
It will gladly do LSTM inference, but the training has to happen in python. I haven’t done much with non-audio effect LSTMs. The very rudimentary example below does a nice job with prediction after it is trained, but I haven’t tried to do anything else. The good news is the plugin is now fairly solid and shouldn’t give you too much trouble.
from my other post:
I have found the best repository for LSTM training to be AutomatedGuitarAmpModeling by Alec Wright, which is written using PyTorch. It is used in Proteus and Aida-x and ChowDSP things. I have found it doesn’t just train guitar amps. It works well with time series things as well. I made an example attached below, which will does time series prediction. I think it could be tweaked to do more complex pitch or word prediction. If not, such scripts certainly exist on GitHub. The python scripts used are included in my repository.
0 is a strange way to ask for the same output length than the querying input. if you ask for AL you would get IC (if lucky ) and if you ask for ALI you would get CES. If you write 5 and query ALI you should get CESIN
now it might be broken, or my understanding might be wrong… so I can check that with the same training you are supposed to get the same thing if you do it manually ALI and ask for 1 and get C so you enter LIC and you should get E and you enter ICE and you get S… @lewardo can you please confirm?
that is what we have here.
Definitely interface will change - not just subject to but will certainly do. So if you need stability for years, you need to go python I think…
in the example I use PyTorch for the training, but if you want to use keras, it will load those models without needing any conversion. That is its lingua franca.
or PyThorch and @spluta 's object for now - all of it is good, the more we find ways to make sense of it and cross patch, the better for my questions above!
@tremblap@spluta – thanks so much !
I’ll look into Sam’s github page. I’m familiar with some implementations of recurrent neural networks in python, but I cannot go python unfortunately – this is a course for musicians for which I cannot assume any familiarity with textual programming. So, that’s not a choice, not even for training.
Can I suggest to get them in in the meantime as “hidden” undocumented objects?
that is what we have here.
Uhm, not really – in order to get them I had to manually patch the package. This isn’t all that elegant for me to propose in the course – or why not, I’m no longer sure.
In any case PA this wasn’t meant to be a trade war
I am just thrilled that there’s a Max-bound RNN object, and I am just a bit sad for the complication to include an example of it in the course, but good things take time. Of course I completely understand your point, of course the interface will change – do whatever is best for Flucoma, I’ll find my way around this!
Thanks for the great work to all of you, and thanks again Sam for the pointers.
Daniele
I didn’t take that for anything else nor worse than good vibes, don’t worry.
For now, this is the interface. It will change, I hope as soon as possible, but this is a massive amount of work. @lewardo replied to me privately, I’m trying to understand it all, in good old FluCoMa fashion (“you only learn for the first time once”).
Not much to add and a bit late to the party, but I did manage to get it to work, but with very poor fitting (though it did improve/change, unlike in your video):
If anyone is interested, I’ve managed to produce a Flucoma patch that takes the Presto from Chopin’s sonata and produces a similar stream of notes via LSTM and temperature.
It’s commented in Italian, but just clicking on 3.4.5.6. shouldn’t need any translation
(1 and 2 are requirements: you need the dataseries objects from flucoma and you need ears for fromsamps/tosamps. You also need bach.)
now now I’m toooooooo excited but I have to finish what I’m working on… will try very soon. @lewardo should be excited too. and I can practice my Italian!
Amazing thread! I’ve been trying to give these modules a go, but I wasn’t able to find the relevant externals for Mac. Is there a link where I can download them? Thanks!