New neural lv2 plugin from Aida DSP based extensively on existing NeuralPi, reduced to the bone

I must have misclicked the “reply” button, cause my comments were about the Epoch amp.

I haven’t tried your creation yet, @madmaxwell but I’d be happy to… if you know of an easy way to run LV2 plugins on Windows :slight_smile:

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https://forum.cockos.com/showthread.php?t=250354

never tested it but I would start reading here. For now supporting daw and vsts would be a bit overkill, for the simply reason now users expect a super polished GUI and I don’t have too much interest in this, I prefer audio.

I consider Mod web ui very good in this sense, I can generate a gui in a minute with their sdk.

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Really nice work @keyth72 ! I compared your EpochAmp to some of my favorite other amps in Amplitube, BiasFX2, ReAmp Studio and Neural DSP. It stacks up pretty well! Mode #2 (“Edge of Breakup” I’m guessing) was the one amp I’d personally use a lot. Just enough breakup, very dynamic, nice EQ. #1 is a nice clean, but it was rather boomy and low level (more than 6dB lower than #2). I could fix it up with a post EQ plugin, but like @Matt said, a tone stack of some sort, even if it was algorithmic instead of profiled would be nice for a future version. Love the look of the UI. One suggestion: because of the shadow effect, the pointers become almost invisible when a knob is at either extreme. The state of the CAB switch is also very difficult to discern. Those are almost forgivable though cuz the louvers for the tube ventilation tells me this is a rockin’ warmth machine. I dig it!

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guys I know things are going crazy here, but would you mind move the discussion about the new plugin from @keyth72 (which I surely think it’s great) in a dedicated thread? I would like to keep things here more focused on plugins compatible with Mod products, possibly feedback on my plugin. It seems this Epoch amp is close source, and no release for Dwarf is available atm.

Regarding my plugin, I would like to share some updates. Me and @spunktsch debugged the opt args for the Dwarf toolchain, finally finding a combination that eliminates noise from the output of the plugin. In other words it means I can now publish a release for Dwarf users, and I’m happy to be able to do it given the circumstances. I hope you can provide feedback on the models available, so that we can adjust and decide what we want to train next.

Have a nice we!

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thanks to @redcloud @spunktsch for the precious help! Posting into plugins too

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just an Update on the live usage of the plugin: worked like a charm and had a good response from friends.
My setup was just the DWARF with the plugin and the mx5 for the fx/ir. Midi switching via ableton. I missed to setup my cam for an audio sample in the room but maybe next time.

Venue was a small room for 60 people - which was packed. Our Sound engineer was glad he only had to dial in one JCM 800. My setup was just straight into the mixer and out to the PA + I got a little more space on stage.


On thing I would do differently the next time is to have a small amp+cab for onstage sound. Notice the sound in the first row was a little lacking.

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With 2023 started and 1.13 on the horizon, let’s revive the enthusiasm for the plugin.
For 1.13 we are adding plugin-specific resource folders, let’s start with the Aida DSP Models.

@madmaxwell how do you feel about the naming, is this ok?

we hope to have most things finalized soon enough that we can start publicly start sharing 1.13 builds.
would be earlier than release candidate, so alike beta releases, but good enough to already begin testing plugin builds against the new compiler/toolchain.

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by the way, since this is plugin specific I made the file type be plugin specific as well.
So change in the main ttl from:

mod:fileTypes "modelsim" ;

to:

mod:fileTypes "aidadspmodel" ;

will share a 1.13 build with this enabled soon.

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Sorry for the late reply busy in the 2023 bring-up. So for the naming I think we should stay with the generic one, modelsim. I mean in my view the author of the model is in the json file together with the other model data. Mine is not even a “custom” format for these neural profiles, since it is just using RTNeural own format. So better to explain a bit. These model files currently part of my rt-neural-generic plugin and in future eventually curated and available on a store for Mod users are the output of a training script that I’ve forked GitHub - MaxPayne86/Automated-GuitarAmpModelling. To be clear it is the same source base as used by GuitarML. The difference is that I have a post-process script that converts the json file from Automated-GuitarAmpModelling into a json file that RTNeural can parse automagically. So that I don’t need to inject weights by hand into the plugin’s sources (like GuitarML does). In turn it also help in tracking regressions between the inference done with pytorch and the inference done by RTNeural. Since convergence problems between different inference engines (I would say libtorch and RTNeural) need to be recognized/tracked. This is my PR on RTNeural to introduce a specific test for this Feature/add test pytorch imported models by MaxPayne86 · Pull Request #79 · jatinchowdhury18/RTNeural · GitHub. That being said, my conversion script can convert also GuitarML models, so in this case it wouldn’t be correct to provide them as Aida DSP’s model files. I won’t do that myself but if anyone want to do it to give these models a shot or if in future other models from other training scripts came out, then would be simply wrong to mark every model as Aida DSP. Hope I’ve explained myself well :wink:

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Sorry if this has been asked, but is there any way I can run this on my mod duo x?

Also: this is an idea I’ve had, but do you think it might be possible to train the model with different knob settings, so that you can simulate the knobs too?

The training data would have different knobs as inputs too, basically.

I tried to set this up a while back (with help from @spunktsch) but we learned the Duo X compiler is too old (error was GLIBC_2.27 not found). Not sure if there’s been any change to this as yet.

I don’t understand enough about it to give any helpful answer. Perhaps @falkTX can advise on this?

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be possible to train the model with different knob settings

Yes it is, just for simplicity we are going with snapshots. The plugin itself with a couple of reverts will support also conditioned models

but we learned the Duo X compiler is too old (error was GLIBC_2.27

Just for you to know, we are now messaging with @falkTX and we’re landing in the store as beta hopefully soon. We’re just fixing bits and test to provide you the best experience. Plugin will run on every device.

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you could also try using this implementation…
might be more efficient / more accurate
github > datkinson/neural-amp-modeler

  • github > sdatkinson/neural-amp-modeler

I tested that already, performance difference is quite striking, I was unable to load simple nam models on the neural-amp-modeler plugin, while the aidadsp with RTNeural backend works well even on a Duo.

Ah that’s interesting. Have you tested most recent update? v0.7.0?

We cant use the official plugin due to it not supporting Linux or LV2.
Instead I tried using GitHub - mikeoliphant/neural-amp-modeler-lv2: Neural Amp Modeler LV2 plugin implementation which in theory works the same way, just in a simpler package.

You can fork Steve’s version or use Mike’s fork of it, because iplug2 has an lv2 branch, and it is MIT licensed. I’m certain Keith is very supportive of Steve’s implementation too - so it’d be great to see the developement of it in Mod ecosystem. That being said, I am happy either way with whatever direction this all goes in - it’s a great time to enjoy playing guitar and having more options for high quality tones.
If you do need anything I’m in touch with Steve and Keith through being the fb moderator - and have a general interest in trying to help or support in anyway I can.
All the best =)

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Keith just posted up some new models in the NAM fb group by the way - you might enjoy trying?

plenty of models here to try too:
github - pelennor2170/NAM_models

I don’t mean to push you out of your way or anything, but this is purely to respond to you saying you couldn’t get NAM models loaded or working. The latest version now only works with single-file format (.nam) and I believe mostly all the pelennor repo is upto date.

All the best!
Dom

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