NAM Model switching logic
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@pratitghosh I think you can use timer node to make a gain node to mute then back to 0 dB to make a smoother transition. This time there will be brief silence every time the knob is tweaked.
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@David-Healey
Interface: F:\Apps\HISE\Projects\API212L\Samples -
@pratitghosh Show us the code for your 5 model version.
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@resonant This is an acceptable result. Silence is manageable. The white noise bursts are unbearable.
Do you have any place where I can learn how to do this? Is this in the HISE Documentation?
(I'm gonna use this technique to make a Manley Voxbox emulation. There are only 5 gain stages... Well, 10 if you count in the Line and Mic switching... And 20 if you count the xfmr in/out switch... But this can be done... I will make that plugin with this idea. As soon as I can do that silence thing, that is.)
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@David-Healey Not a lot of code, I'm doing this 5-model thing in a new project. Here is the code and the scriptnode.
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@pratitghosh Aha I see. Using that method you don't need any scripting because you can load the models directly in scriptnode, no? But also I don't think you can implement the timer idea with this method.
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@pratitghosh yes documentation will be helpful.
Are you using Nam or Aida x? Nam is very cpu extensive in stereo processing. How do you prevent this?
Also can you embed models as json scripts intı the plugin, or external files? -
@David-Healey
Why is NAM like this... Just give us normies a nice loadModel function in a simple cpp that we can just put in a third party C++ node of our own like#include "./loader.cpp";
Network.loadModel(index+".nam");And Boom, job done.
But nooooooo, it has to be convoluted.
(Sorry for the rant I know it's a lot more complex than that)
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@resonant I'm not preventing s#it... I'm just testing out the waters. So 35-40% CPU usage isn't as big of an issue right now. Just trying to see if my idea can actually be realised. Also what's Aida x?
As much as I gathered from other chats in this forum, you can embed models as json scripts. I'm not sure, as a noob, if I'll be able to do it or not... So I am just going the simplest route I can take and kinda brute forcing it to work.
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@pratitghosh Remove these two lines of code
Can you share a minimal project with 5 nam models and your script for loading them with the drive knob?
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@David-Healey Sorry I didn't understand what you mean. Do you want the project where I made that 5 model scriptnode thing? That's in a project called "API", which I made like a few minutes ago after seeing resonant's idea. Meanwhile the neuralNetwork code is from a project called TestPre, which I was working on originally.
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@pratitghosh I want you to make a new project, add 5 models to it. Add the switcher script you showed in your first post (TestPre). Compress it to a zip file, upload it somewhere, and post a link here.
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@David-Healey Aye aye, cap'n.
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Well apparently you can just upload zips straight into this forum. Neat.
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@pratitghosh said in NAM Model switching logic:
@resonant Also what's Aida x?
It’s a cpu friendly alternative to nam. Not sure if it is more accurate than nam but it is pretty good. It works in Hise too.
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Ok I understand what the issue is now. I hadn't worked with neural nodes before so the terminology was confusing me slightly.
So according to Christoph you can't change the model at runtime in a single neural node through scripting. You need to do as @resonant said and create multiple nodes with 1 model loaded into each.
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@David-Healey In the same conversation there are 2 replies from scottmire and sinewavekid... Do you have any information on those?
Using a script to change between neural networks? Or using clearModel() to load a new network?
Or if not that either, can you help with the timer to silence thing?
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@pratitghosh said in NAM Model switching logic:
Do you have any information on those?
then I could follow with a new "NeuralNetwork.loadTensorFlowModel( var modelJSON)" function call. It obviously doesn't work this way.....but it would be amazing if it could....just sayin...lol.
I don't know how you could use the timer with a network
