Neural Amp Modeler (NAM) in HISE

[Christoph Hart]

@Dan-Korneff more like January 17th..

[Dan Korneff]

@Christoph-Hart

[Sclass]

Any updates?

[Christoph Hart]

@Sclass nope, working on other stuff.

[Sclass]

@Christoph-Hart Still keeping an eye out for the NAM update :)

[Lurch]

@Christoph-Hart Any news? This would be an amazing addition to HISE.

[aaronventure]

@Lurch I mean, it works? The performance is seemingly twice as bad as the NAM plugin, but only because the neural node in HISE is processing two channels, and the NAM plugin is processing one.

If you use the multi node to force mono processing and before that collapse the stereo signal into mono, you get roughly the same performance.

Create your NAM file in the colab https://colab.research.google.com/github/sdatkinson/NAMTrainerColab/blob/main/notebook.ipynb

Put in into the Samples directory.

const neuralNetwork = Engine.createNeuralNetwork("MidDrive");

const namModel = FileSystem.getFolder(FileSystem.Samples).getChildFile("model.nam").loadAsObject();

neuralNetwork.loadNAMModel(namModel);

Create a ScriptFX DSPNetwork and load the math.neural node.

It would be cool to be able to embed the .nam files into the plugin instead of having to install them separately.

[Christoph Hart]

@aaronventure said in Neural Amp Modeler (NAM) in HISE:

If you use the multi node to force mono processing and before that collapse the stereo signal into mono, you get roughly the same performance.

Haha wasn't all that drama about it being 8x slower than the NAM plugin?

It would be cool to be able to embed the .nam files into the plugin instead of having to install them separately.

Can't you just embed the JSON content of the NAM file into a script and it will be embedded in the plugin?

[aaronventure]

@Christoph-Hart said in Neural Amp Modeler (NAM) in HISE:

Haha wasn't all that drama about it being 8x slower than the NAM plugin?

I have no idea, I'm only now touching it for the first time.

I ran direct comparisons in Reaper and a Waveform Synth with NAM on stereo channels consumes 1% of CPU (20% of RT CPU), while two NAM plugins in total consume 0.9% of CPU and 18% of RT CPU.

So HISE is about 10% less efficient, which is good enough and entirely shippable if you ask me.

@Christoph-Hart said in Neural Amp Modeler (NAM) in HISE:

Can't you just embed the JSON content of the NAM file into a script and it will be embedded in the plugin?

I sure can. I feel silly now. Thank you.

[Orvillain]

@aaronventure

I'm seeing about 25% here with this. Not sure I understood about the multi container thing.

[aaronventure]

@Orvillain you can still see the two cables going into it. You multi node should contain a neural node and an empty chain node.

[whoopsydoodle]

How well does this nam implementation handle different sample rates? I know some get tripped up if you try to run a sample rate that's different than what your model was trained on.

[scottmire]

Strange....
I'm getting a "function not found" error when calling loadNAMModel