Update NeuralAudio (fix composite model receptive field)

Oversampling support

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,17 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is. Please do not include AI chat transcripts.
+
+**Environment**
+Please include information on the operating system and plugin host environment where you are experiencing the issue. If you can, please test in multiple different contexts (ie: different DAWs)
+
+**Additional Information**
+Please add any additional detail here.

.github/workflows/build.yml

@@ -20,10 +20,14 @@ jobs:
       env:
         CXX: clang++
       run: |
-        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE
+        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE -DBUILD_UTILS=ON -DBUILD_INTERNAL_STATIC_WAVENET=ON -DBUILD_INTERNAL_STATIC_LSTM=ON -DBUILD_NAMCORE=ON -DBUILD_STATIC_RTNEURAL=ON 
         cmake --build . --config $BUILD_TYPE -j4
         cpack
 
+    - name: Run ModelTest
+      working-directory: ${{github.workspace}}/build/src/NeuralAudio/Utils/ModelTest
+      run: ./ModelTest
+      
     - name: Upload binary
       uses: actions/upload-artifact@v4
       with:
@@ -47,9 +51,13 @@ jobs:
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
       run: |
-        cmake.exe -G "Visual Studio 17 2022" -A x64  -T ClangCL ..
+        cmake.exe -G "Visual Studio 18 2026" -A x64 -DBUILD_UTILS=ON -DBUILD_INTERNAL_STATIC_WAVENET=ON -DBUILD_INTERNAL_STATIC_LSTM=ON -DBUILD_NAMCORE=ON -DBUILD_STATIC_RTNEURAL=ON -T ClangCL ..
         cmake --build . --config=release -j4
 
+    - name: Run ModelTest
+      working-directory: ${{github.workspace}}/build/src/NeuralAudio/Utils/ModelTest/Release
+      run: ./ModelTest.exe
+        
     - name: Upload artifact
       uses: actions/upload-artifact@v4
       with:

.github/workflows/release.yml

@@ -31,7 +31,12 @@ jobs:
   build-linux-x64:
     name: Build Linux x64
     needs: create_release
+    strategy:
+      matrix:
+        native_arch: [ON, OFF]
     runs-on: ubuntu-latest
+    env:
+      ARCHIVE_NAME: neural_amp_modeler_lv2_linux_x64${{ matrix.native_arch == 'ON' && 'v3' || '' }}.tgz
     steps:
     - uses: actions/checkout@v3.3.0
       with:
@@ -42,12 +47,12 @@ jobs:
       env:
         CXX: clang++
       run: |
-        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE
+        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE -DUSE_NATIVE_ARCH=${{ matrix.native_arch }} -DBUILD_NAMCORE=ON -DBUILD_INTERNAL_STATIC_WAVENET=ON -DBUILD_INTERNAL_STATIC_LSTM=ON
         cmake --build . --config $BUILD_TYPE -j4
 
     - name: Add LV2 Archive
       working-directory: ${{github.workspace}}/build
-      run: tar -czf neural_amp_modeler_lv2_linux_x64.tgz neural_amp_modeler.lv2
+      run: tar -czf ${{ env.ARCHIVE_NAME }} neural_amp_modeler.lv2
       
     - name: Upload Plugin Asset
       uses: actions/upload-release-asset@v1
@@ -55,14 +60,21 @@ jobs:
         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       with:
         upload_url: ${{ needs.create_release.outputs.upload_url }}
-        asset_path: ./build/neural_amp_modeler_lv2_linux_x64.tgz
+        asset_path: ./build/${{ env.ARCHIVE_NAME }}
-        asset_name: neural_amp_modeler_lv2_linux_x64.tgz
+        asset_name: ${{ env.ARCHIVE_NAME }}
         asset_content_type: application/tgz
 
-  build-linux-x64v3:
+  build-rpi:
-    name: Build Linux x64v3
+    name: Build Raspberry Pi
     needs: create_release
+    strategy:
+      matrix:
+        native_arch: [rpi4, rpi5]
     runs-on: ubuntu-latest
+    container: 
+      image: ghcr.io/tttapa/docker-arm-cross-toolchain:aarch64-rpi3-linux-gnu-gcc12
+    env:
+      ARCHIVE_NAME: neural_amp_modeler_lv2_${{ matrix.native_arch }}.tgz
     steps:
     - uses: actions/checkout@v3.3.0
       with:
@@ -70,15 +82,13 @@ jobs:
     
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
-      env:
-        CXX: clang++
       run: |
-        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE -DUSE_NATIVE_ARCH=ON
+        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE -DBUILD_NAMCORE=ON -DBUILD_INTERNAL_STATIC_WAVENET=ON -DBUILD_INTERNAL_STATIC_LSTM=ON -DCMAKE_TOOLCHAIN_FILE=/home/develop/opt/x-tools/aarch64-rpi3-linux-gnu/aarch64-${{ matrix.native_arch }}-linux-gnu.toolchain.cmake
         cmake --build . --config $BUILD_TYPE -j4
 
     - name: Add LV2 Archive
       working-directory: ${{github.workspace}}/build
-      run: tar -czf neural_amp_modeler_lv2_linux_x64v3.tgz neural_amp_modeler.lv2
+      run: tar -czf ${{ env.ARCHIVE_NAME }} neural_amp_modeler.lv2
       
     - name: Upload Plugin Asset
       uses: actions/upload-release-asset@v1
@@ -86,14 +96,19 @@ jobs:
         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       with:
         upload_url: ${{ needs.create_release.outputs.upload_url }}
-        asset_path: ./build/neural_amp_modeler_lv2_linux_x64v3.tgz
+        asset_path: ./build/${{ env.ARCHIVE_NAME }}
-        asset_name: neural_amp_modeler_lv2_linux_x64v3.tgz
+        asset_name: ${{ env.ARCHIVE_NAME }}
         asset_content_type: application/tgz
         
   build-windows:
     name: Build Windows
     needs: create_release
+    strategy:
+      matrix:
+        native_arch: [ON, OFF]
     runs-on: windows-latest
+    env:
+      ARCHIVE_NAME: neural_amp_modeler_lv2_win_x64${{ matrix.native_arch == 'ON' && 'v3' || '' }}.zip
     steps:
     - uses: actions/checkout@v3.3.0
       with:
@@ -102,11 +117,11 @@ jobs:
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
       run: |
-        cmake.exe -G "Visual Studio 17 2022" -A x64  -T ClangCL ..
+        cmake.exe -G "Visual Studio 18 2026" -A x64  -T ClangCL -DUSE_NATIVE_ARCH=${{ matrix.native_arch }} -DBUILD_NAMCORE=ON -DBUILD_INTERNAL_STATIC_WAVENET=ON -DBUILD_INTERNAL_STATIC_LSTM=ON ..
         cmake --build . --config=release -j4
 
     - name: Add LV2 Archive
-      run: Compress-Archive -Path ${{github.workspace}}\build\neural_amp_modeler.lv2 -Destination neural_amp_modeler_lv2_win_x64.zip
+      run: Compress-Archive -Path ${{github.workspace}}\build\neural_amp_modeler.lv2 -Destination ${{ env.ARCHIVE_NAME }}
       
     - name: Upload Plugin Asset
       uses: actions/upload-release-asset@v1
@@ -114,34 +129,6 @@ jobs:
         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       with:
         upload_url: ${{ needs.create_release.outputs.upload_url }}
-        asset_path: ./neural_amp_modeler_lv2_win_x64.zip
+        asset_path: ./${{ env.ARCHIVE_NAME }}
-        asset_name: neural_amp_modeler_lv2_win_x64.zip
+        asset_name: ${{ env.ARCHIVE_NAME }}
-        asset_content_type: application/zip
-
-  build-windows-x64v3:
-    name: Build Windows x64v3
-    needs: create_release
-    runs-on: windows-latest
-    steps:
-    - uses: actions/checkout@v3.3.0
-      with:
-        submodules: recursive
-    
-    - name: Build Plugin
-      working-directory: ${{github.workspace}}/build
-      run: |
-        cmake.exe -G "Visual Studio 17 2022" -A x64 -DUSE_NATIVE_ARCH=ON -T ClangCL ..
-        cmake --build . --config=release -j4
-
-    - name: Add LV2 Archive
-      run: Compress-Archive -Path ${{github.workspace}}\build\neural_amp_modeler.lv2 -Destination neural_amp_modeler_lv2_win_x64v3.zip
-      
-    - name: Upload Plugin Asset
-      uses: actions/upload-release-asset@v1
-      env:
-        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      with:
-        upload_url: ${{ needs.create_release.outputs.upload_url }}
-        asset_path: ./neural_amp_modeler_lv2_win_x64v3.zip
-        asset_name: neural_amp_modeler_lv2_win_x64v3.zip
         asset_content_type: application/zip

CMakeLists.txt

@@ -1,8 +1,9 @@
 cmake_minimum_required(VERSION 3.10)
 
-project(NeuralAmpModelerLv2 VERSION 0.1.6)
+project(NeuralAmpModelerLv2 VERSION 0.2.0)
 
 set(CMAKE_MODULE_PATH "${CMAKE_SOURCE_DIR}/cmake")
+set(LIB_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib CACHE PATH "The library install dir (default: lib)")
 
 set(CMAKE_CXX_STANDARD 20)
 set(CMAKE_CXX_STANDARD_REQUIRED OFF)
@@ -11,7 +12,7 @@ set(CMAKE_CXX_EXTENSIONS OFF)
 if (CMAKE_SYSTEM_NAME STREQUAL "Darwin")
 	include_directories(SYSTEM /usr/local/include)
 elseif (CMAKE_SYSTEM_NAME STREQUAL "Linux")
-	link_libraries(stdc++fs)
+	link_libraries( "$<$<AND:$<CXX_COMPILER_ID:GNU>,$<VERSION_LESS:$<CXX_COMPILER_VERSION>,9.0>>:-lstdc++fs>" )
 elseif (CMAKE_SYSTEM_NAME STREQUAL "Windows")
 	add_compile_definitions(NOMINMAX WIN32_LEAN_AND_MEAN)
 else()
@@ -29,11 +30,14 @@ add_custom_target(copy_binaries ALL
 	DEPENDS neural_amp_modeler
 )
 
+file(COPY resources/modgui.ttl DESTINATION neural_amp_modeler.lv2)
+file(COPY resources/modgui DESTINATION neural_amp_modeler.lv2)
+
 configure_file(resources/manifest.ttl.in neural_amp_modeler.lv2/manifest.ttl)
 configure_file(resources/neural_amp_modeler.ttl.in neural_amp_modeler.lv2/neural_amp_modeler.ttl)
 
 install (DIRECTORY ${CMAKE_BINARY_DIR}/neural_amp_modeler.lv2
-       DESTINATION lib/lv2
+       DESTINATION ${LIB_INSTALL_DIR}/lv2
 )
 
 set(CPACK_GENERATOR "DEB")

CREDITS.md

@@ -1,11 +1,11 @@
-This repository uses code from a number of sources:
+[GitHub contributers](https://github.com/mikeoliphant/neural-amp-modeler-lv2/graphs/contributors)
 
-https://github.com/sdatkinson/NeuralAmpModelerCore
+This repository uses code from a number of sources. Please see them for code licensing information:
 
-https://gitlab.com/libeigen/eigen
+https://github.com/mikeoliphant/NeuralAudio
-
-https://github.com/jatinchowdhury18/RTNeural
 
 https://github.com/lv2/lv2
 
-In addition, the CMake structure and LV2 plugin structure are based on code from https://github.com/Dougal-s/Aether.
+The CMake structure and LV2 plugin structure are based on code from https://github.com/Dougal-s/Aether.
+
+modgui user interface is by Roman Brandstetter (@rominator1983) and Filipe Coelho (@falktk) based on design from Evan Heritage.

README.md

@@ -1,33 +1,39 @@
 # neural-amp-modeler-lv2
 
-LV2 plugin for using neural network machine learning amp models.
+LV2 plugin for neural network machine learning amp model playback using the [NeuralAudio](https://github.com/mikeoliphant/NeuralAudio) engine.
 
 **There is no custom plugin user interface**. Setting the model to use requires that your LV2 host supports atom:Path parameters. Reaper does as of v6.82. Carla and Ardour do. If your favorite LV2 host does not support atom:Path, let them know you want it.
-If you are looking for a GUI version, @brummer10 [has one here](https://github.com/brummer10/neural-amp-modeler-ui) that works for Linux and Windows. You may also be interested in the the version shipped with the [MOD Desktop App](https://github.com/moddevices/mod-desktop-app), or my digital pedalboard app [Stompbox](https://github.com/mikeoliphant/StompboxUI).
+If you are looking for a GUI version, @brummer10 [has one here](https://github.com/brummer10/neural-amp-modeler-ui) that works for Linux and Windows. You may also be interested in the the version shipped with the [MOD Desktop App](https://github.com/moddevices/mod-desktop-app), or my digital pedalboard app [Stompbox](https://github.com/mikeoliphant/Stompbox).
 
 To get the intended behavior, **you must run your audio host at the same sample rate the model was trained at** (usually 48kHz) - no resampling is done by the plugin.
 
 For amp-only models (the most typical), **you will need to run an impulse reponse after this plugin** to model the cabinet.
 
-### Models and Performance
+## Usage
 
-The plugin supports both [Neural Amp Modeler (NAM)](https://github.com/sdatkinson/neural-amp-modeler) models and [RTNeural keras json models](https://github.com/jatinchowdhury18/RTNeural) (like those used by [Aida-X](https://github.com/AidaDSP/AIDA-X)).
+Your DAW should expose the following input controls:
 
-The best source of models is [ToneHunt](https://tonehunt.org/).
+**Input:** - Input (pre-model) gain in dB.
 
-NAM WaveNet models are generally quite expensive to run. This isn't (much of) an issue on modern PCs, but you may have trouble running on less powerful hardware.
+**Output:** - Output (post-model) volume in dB.
 
-A Raspberry Pi 4 running a 64bit OS can run "standard" NAM models with a bit of room to spare for a cabinet IR and some lightweight effects.
+**Quality:** - Model quality (if applicable). For NAM A2 models, a value below 0.5 will give you a "lite" model and a value above 0.5 will give you a "full" model.
 
-If you are having trouble running a "standard" model, try looking for "feather", or even "nano" (the least expensive) models. You can find a list of ["feather"-tagged models on ToneHunt](https://tonehunt.org/models?tags%5B0%5D=feather-mdl). Note that tagging models is up to the submitter, so not all "feather" models are tagged as such - you should be able to find more if you dig around.
+**Model:** - The model file (ie: xxx.nam) to use.
 
-For more information on model type support, see the [NeuralAudio](https://github.com/mikeoliphant/NeuralAudio) repository, which is where the model handling code lives.
+## Models Supported and Performance
+
+The plugin supports both [Neural Amp Modeler (NAM)](https://github.com/sdatkinson/neural-amp-modeler) models (both A1 and A2) and [RTNeural keras json models](https://github.com/jatinchowdhury18/RTNeural) (like those used by [Aida-X](https://github.com/AidaDSP/AIDA-X)).
+
+The best source of models is [Tone3000](https://www.tone3000.com/).
+
+For more information on model type support and performance, see the [NeuralAudio](https://github.com/mikeoliphant/NeuralAudio) repository, which is where the model handling code lives.
 
 ## Input Calibration
 
 The expected input level to the plugin is 12dBu. For models that include input level information, they will be calibrated against this level. If you know the input level of your audio interface, you should adjust the input level relative to the expected 12dBu to provide the appropriate signal level to the model.
 
-### Building
+## Building
 
 First clone the repository:
 ```bash
@@ -53,8 +59,10 @@ Note - you'll have to change the Visual Studio version if you are using a differ
 
 After building, the plugin will be in **build/neural_amp_modeler.lv2**.
 
-### Optimization
+## CMake Options
 
-If you have a relatively modern x64 processor, you can pass ```-DUSE_NATIVE_ARCH=ON``` on your cmake command line to enable certain processor-specific optimizations.
+```-DUSE_NATIVE_ARCH=ON```: If you have a relatively modern x64 processor, you can pass ```-DUSE_NATIVE_ARCH=ON``` on your cmake command line to enable certain processor-specific optimizations.
 
-You can also alter the default model loading behavior with ```-DLSTM_PREFER_NAM=ON``` (use NAM Core instead of RTNeural for NAM LSTM models) and ```-DWAVENET_PREFER_NAM=ON``` (use NAM Core instead of RTNeural or NAM WaveNet models).
+```-DSMART_BYPASS_ENABLED=ON```: If enabled, this will bypass model processing if input has been silent (below -100 dB by default) for a sufficient number of samples (determined by the model's receptive field size).
+
+Also see the [NeuralAudio CMake options](https://github.com/mikeoliphant/NeuralAudio#cmake-options) - adding these to your neural-amp-modeler-lv2 cmake will pass them to the NeuralAudio build.

models/README.md

@@ -1,12 +0,0 @@
-These are some sample NAM models designed to be used for performance testing on CPU-limited devices. They are all based on a [LiveSpice model of a Boss SD-1 pedal](https://blog.nostatic.org/2023/04/this-boss-sd-1-pedal-does-not-exist.html).
-
-All models were trained for 300 epochs using the NAM "v1_1_1.wav" capture signal.
-
-| Model | ESR | CPU%<br>(RPi4 64bit) | Notes |
-| --- |--- | :-: | --- |
-| [BossWN-feather.nam](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/models/BossWN-feather.nam) | .0001 | 37% | WaveNet "feather" preset |
-| [BossWN-4x2x1.nam](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/models/BossWN-4x2x1.nam) | .0003 | 28% | WaveNet 4x2 channel |
-| [BossLSTM-2x16.nam](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/models/BossLSTM-2x16.nam) | .0013 | 28% | LSTM 2x16 layers |
-| [BossLSTM-1x24.nam](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/models/BossLSTM-1x24.nam) | .0017 | 22% | LSTM 1x24 layer |
-| [BossLSTM-2x8.nam](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/models/BossLSTM-2x8.nam) | .0019 | 17% | LSTM 2x8 layers |
-| [BossLSTM-1x16.nam](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/models/BossLSTM-1x16.nam) | .0041 | 15% | LSTM 1x16 layer |

resources/manifest.ttl.in

@@ -5,4 +5,4 @@
 <@NAM_LV2_ID@>
 	a lv2:Plugin;
 	lv2:binary <neural_amp_modeler@CMAKE_SHARED_MODULE_SUFFIX@>;
-	rdfs:seeAlso <neural_amp_modeler.ttl>.
+	rdfs:seeAlso <neural_amp_modeler.ttl>,<modgui.ttl>.

resources/modgui.ttl

@@ -0,0 +1,21 @@
+@prefix modgui: <http://moddevices.com/ns/modgui#>.
+@prefix lv2:    <http://lv2plug.in/ns/lv2core#>.
+
+<http://github.com/mikeoliphant/neural-amp-modeler-lv2>
+    modgui:gui [
+        modgui:resourcesDirectory <modgui>;
+        modgui:iconTemplate <modgui/icon-nam.html>;
+        modgui:stylesheet <modgui/stylesheet-nam.css>;
+        modgui:screenshot <modgui/screenshot-nam.png>;
+        modgui:thumbnail <modgui/thumbnail-nam.png>;
+        modgui:discussionURL <https://forum.mod.audio/t/neural-amp-modeler/10112> ;
+        modgui:port [
+            lv2:index 0;
+            lv2:symbol "input_level";
+            lv2:name "Input Lvl";
+        ], [
+            lv2:index 1;
+            lv2:symbol "output_level";
+            lv2:name "Output Lvl";
+        ];
+    ].

resources/modgui/icon-nam.html

@@ -0,0 +1,45 @@
+<div class="mod-pedal mod-pedal-nam">
+    <div mod-role="drag-handle" class="mod-drag-handle"></div>
+    <div class="mod-control-group group1 clearfix">
+        {{#controls}}
+        <div class="mod-knob" title="{{name}}">
+            <div class="mod-knob-title">{{name}}</div>
+            <div class="mod-knob-image" mod-role="input-control-port" mod-port-symbol="{{symbol}}"></div>
+        </div>
+        {{/controls}}
+    </div>
+    <div class="mod-footswitch" mod-role="bypass"></div>
+
+    <div class="mod-control-group group2 clearfix">
+        <div class="mod-control-group mod-enumerated-group bottom clearfix">
+            {{#effect.parameters}}
+            {{#path}}
+            <div class="mod-enumerated" mod-role="input-parameter" mod-parameter-uri="{{uri}}" mod-widget="custom-select-path">
+                <div mod-role="input-parameter-value" mod-parameter-uri="{{uri}}" class="mod-enumerated-selected">
+                    -- choose a NAM model --
+                </div>
+                <div class="mod-enumerated-list">
+                    {{#files}}
+                    <div mod-role="enumeration-option" mod-parameter-value="{{fullname}}">{{basename}}</div>
+                    {{/files}}
+                </div>
+            </div>
+            {{/path}}
+            {{/effect.parameters}}
+        </div>
+    </div>
+    <div class="mod-pedal-input">
+        {{#effect.ports.audio.input}}
+        <div class="mod-input mod-input-disconnected" title="{{name}}" mod-role="input-audio-port" mod-port-symbol="{{symbol}}">
+            <div class="mod-pedal-input-image"></div>
+        </div>
+        {{/effect.ports.audio.input}}
+    </div>
+    <div class="mod-pedal-output">
+        {{#effect.ports.audio.output}}
+        <div class="mod-output mod-output-disconnected" title="{{name}}" mod-role="output-audio-port" mod-port-symbol="{{symbol}}">
+            <div class="mod-pedal-output-image"></div>
+        </div>
+        {{/effect.ports.audio.output}}
+    </div>
+</div>

resources/modgui/stylesheet-nam.css

@@ -0,0 +1,130 @@
+/* nam */
+
+@import url(/fonts/nexa/stylesheet.css);
+@import url(/fonts/questrial/stylesheet.css);
+
+/* = CONTAINER
+================================================ */
+.mod-pedal-nam {
+    background-position:center center;
+    background-repeat:no-repeat;
+    /* background image is 1121 × 536*/
+    background-size:560px 268px;
+    background-image:url(/resources/background.png{{{ns}}});
+    width:560px;
+    height:268px;
+    position:absolute;
+    border-radius:40px;
+}
+
+/* = BYPASS
+================================================ */
+.mod-pedal-nam .mod-footswitch {
+    background-image:url(/resources/bypass_on.png{{{ns}}});
+    background-position:center center;
+    background-repeat:no-repeat;
+    background-size:82px 47px;
+    width:82px;
+    height:47px;
+    top:132px;
+    left:235px;
+    cursor:pointer;
+    position:absolute;
+}
+.mod-pedal-nam .mod-footswitch.on {
+    background-image:url(/resources/bypass_off.png{{{ns}}});
+}
+
+/* = KNOBS
+================================================ */
+.mod-pedal-nam .mod-control-group {
+    z-index:30;
+    position:relative;
+    margin:0px;
+    padding:0px;
+    display:inline;
+}
+
+.mod-pedal-nam .group1 {
+    top:86px;
+    left:22px;
+}
+
+.mod-pedal-nam .group2 {
+    top:107px;
+    left:78px;
+}
+
+.mod-pedal-nam .mod-control-group .mod-knob .mod-knob-title {
+    text-align: center;
+    color:white;
+}
+
+.mod-pedal-nam .mod-control-group .mod-knob {
+    overflow:hidden;
+    position:relative;
+    display:inline-block;
+}
+
+.mod-pedal-nam .mod-control-group .mod-knob:first-child {
+    margin-left: 0px;
+}
+
+.mod-pedal-nam .mod-control-group .mod-knob:last-child {
+    margin-left: 315px;
+}
+
+.mod-pedal-nam .mod-control-group .mod-knob .mod-knob-image {
+    background-image:url(/resources/knob.png{{{ns}}});
+    background-position:left center;
+    background-repeat:no-repeat;
+    background-size:5000px 100px;
+    height:100px;
+    width:100px;
+    cursor:pointer;
+}
+
+.mod-pedal-nam .mod-enumerated {
+    position: relative;
+    font-weight: bold;
+    cursor: pointer;
+    color: white;
+}
+
+.mod-pedal-nam .mod-enumerated .mod-enumerated-selected {
+    padding-left: 5px;
+    overflow: hidden;
+    white-space: nowrap;
+    text-overflow: ellipsis;
+    background-color: transparent;
+    color: white;
+    display: block;
+}
+
+/* THE LIST OF OPTIONS */
+.mod-pedal-nam .mod-enumerated .mod-enumerated-list {
+    background: black;
+    display: none;
+    overflow: auto;
+    position: absolute;
+    padding: 0;
+    width: 405px;
+    height: 220px;
+    border: 2px solid #333;
+}
+
+.mod-pedal-nam .mod-enumerated .mod-enumerated-list > div {
+    padding: 3px 5px;
+}
+
+.mod-pedal-nam .mod-enumerated .mod-enumerated-list > div.selected {
+    background: #333;
+}
+
+.mod-pedal-nam .mod-enumerated .mod-enumerated-list > div:hover {
+    background: #222;
+}
+
+.mod-pedal-nam .mod-enumerated .mod-enumerated-list > div.selected:hover {
+    background: #555;
+}

resources/neural_amp_modeler.ttl.in

@@ -16,7 +16,7 @@
 
 <@NAM_LV2_ID@#model>
 	a lv2:Parameter;
-	mod:fileTypes "nam,nammodel,json,aidax";
+	mod:fileTypes "nam,nammodel,json,aidax,aidadspmodel";
 	rdfs:label "Neural Model";
 	rdfs:range atom:Path.
 
@@ -45,7 +45,7 @@ Models supported:
   Neural Amp Modeler (NAM): https://github.com/sdatkinson/neural-amp-modeler
   RTNeural keras/Aida-x models: https://github.com/jatinchowdhury18/RTNeural
 
-A large collection of models is available at https://tonehunt.org
+A large collection of models is available at https://www.tone3000.com
 """;
 
 	patch:writable <@NAM_LV2_ID@#model>;
@@ -101,4 +101,12 @@ A large collection of models is available at https://tonehunt.org
 		lv2:minimum -20.0;
 		lv2:maximum 20.0;
 		units:unit units:db;
+	], [
+		a lv2:ControlPort, lv2:InputPort;
+		lv2:index 6;
+		lv2:symbol "quality_scale";
+		lv2:name "Quality";
+		lv2:default 1.0;
+		lv2:minimum 0.0;
+		lv2:maximum 1.0;
 	].

src/CMakeLists.txt

@@ -18,8 +18,14 @@ if (CMAKE_SYSTEM_PROCESSOR MATCHES "(amd64)|(AMD64)|(x86_64)")
 	option(USE_NATIVE_ARCH "Enable architecture-specific optimizations" OFF)
 
 	if (USE_NATIVE_ARCH)
+		if (CMAKE_CXX_COMPILER_ID STREQUAL "MSVC")
+			add_compile_options(/arch:AVX2)
+			message(STATUS "Enabling /arch:AVX2")
+		 
+		else()
 			add_compile_options(-march=x86-64-v3)
-		message("Enabling -march=x86-64-v3")
+			message(STATUS "Enabling -march=x86-64-v3")
+		endif()
 	endif (USE_NATIVE_ARCH)
 endif ()
 
@@ -48,23 +54,14 @@ if (DISABLE_DENORMALS)
 	add_definitions(-DDISABLE_DENORMALS)
 endif (DISABLE_DENORMALS)
 
-option(LSTM_PREFER_NAM "Always use NAM Core for NAM LSTM models" ON)
+option(SMART_BYPASS_ENABLED "Enable auto-bypass on silence" OFF)
 
-if (LSTM_PREFER_NAM)
+if (SMART_BYPASS_ENABLED)
-	add_definitions(-DLSTM_PREFER_NAM)
+	add_definitions(-DSMART_BYPASS_ENABLED)
-	message("Using NAM Core for LSTM models")
+	message(STATUS "Smart Bypass enabled")
 else()
-	message("Using RTNeural for LSTM models")
+	message(STATUS "Smart Bypass NOT enabled")
-endif (LSTM_PREFER_NAM)
+endif (SMART_BYPASS_ENABLED)
-
-option(WAVENET_PREFER_NAM "Always use NAM Core for NAM WaveNet models" OFF)
-
-if (WAVENET_PREFER_NAM)
-	add_definitions(-DWAVENET_PREFER_NAM)
-	message("Using NAM Core for WaveNet models")
-else()
-	message("Using RTNeural for WaveNet models")
-endif (WAVENET_PREFER_NAM)
 
 set_target_properties(neural_amp_modeler
 	PROPERTIES

src/nam_plugin.cpp

@@ -7,27 +7,33 @@
 
 #define SMOOTH_EPSILON .0001f
 
+#ifndef BYPASS_DB_THRESHOLD
+#define BYPASS_DB_THRESHOLD -100
+#endif
+
 namespace NAM {
 	Plugin::Plugin()
 	{
 		// prevent allocations on the audio thread
 		currentModelPath.reserve(MAX_FILE_NAME + 1);
 
-		NeuralAudio::NeuralModel::SetLSTMLoadMode(
+		bypassThresholdLinear = powf(10, BYPASS_DB_THRESHOLD * 0.05f);
-#ifdef LSTM_PREFER_NAM
-			NeuralAudio::PreferNAMCore
-#else
-			NeuralAudio::PreferRTNeural
-#endif
-		);
 
-		NeuralAudio::NeuralModel::SetWaveNetLoadMode(
+//		NeuralAudio::NeuralModel::SetLSTMLoadMode(
-#ifdef WAVENET_PREFER_NAM
+//#ifdef LSTM_PREFER_NAM
-			NeuralAudio::PreferNAMCore
+//			NeuralAudio::PreferNAMCore
-#else
+//#else
-			NeuralAudio::PreferRTNeural
+//			NeuralAudio::PreferRTNeural
-#endif
+//#endif
-		);
+//		);
+//
+//		NeuralAudio::NeuralModel::SetWaveNetLoadMode(
+//#ifdef WAVENET_PREFER_NAM
+//			NeuralAudio::PreferNAMCore
+//#else
+//			NeuralAudio::PreferRTNeural
+//#endif
+		//);
 	}
 
 	Plugin::~Plugin()
@@ -39,6 +45,8 @@ namespace NAM {
 	{
 		this->sampleRate = sampleRate;
 
+		loader.SetExternalSampleRate((int)sampleRate);
+
 		// for fetching initial options, can be null
 		LV2_Options_Option* options = nullptr;
 
@@ -122,7 +130,7 @@ namespace NAM {
 					{
 						lv2_log_trace(&nam->logger, "Staging model change: `%s`\n", msg->path);
 
-						model = NeuralAudio::NeuralModel::CreateFromFile(msg->path);
+						model = nam->loader.CreateFromFile(msg->path);
 					}
 
 					if (model != nullptr)
@@ -181,6 +189,18 @@ namespace NAM {
 		nam->currentModelPath = msg->path;
 		assert(nam->currentModelPath.capacity() >= MAX_FILE_NAME + 1);
 
+		if (nam->currentModel != nullptr)
+		{
+			int receptiveFieldSize = nam->currentModel->GetReceptiveFieldSize();
+
+			if (receptiveFieldSize > -1)
+			{
+				// A newly loaded model is prewarmed to have a silent sample history
+				nam->silentSamples = receptiveFieldSize;
+				nam->smartBypassed = true;
+			}
+		}
+
 		// send reply
 		nam->schedule->schedule_work(nam->schedule->handle, sizeof(reply), &reply);
 
@@ -194,7 +214,7 @@ namespace NAM {
 	{
 		maxBufferSize = size;
 
-		NeuralAudio::NeuralModel::SetDefaultMaxAudioBufferSize(size);
+		loader.SetDefaultMaxAudioBufferSize(size);
 	}
 
 	void Plugin::process(uint32_t n_samples) noexcept
@@ -234,6 +254,18 @@ namespace NAM {
 			}
 		}
 
+		if (*(ports.quality_scale) != qualityScale)
+		{
+			qualityScale = *(ports.quality_scale);
+
+			loader.SetDefaultQualityScaleFactor(qualityScale);
+
+			if (currentModel != nullptr)
+			{
+				currentModel->SetQualityScaleFactor(qualityScale);
+			}
+		}
+
 		float level;
 
 		float modelInputAdjustmentDB = 0;
@@ -241,6 +273,44 @@ namespace NAM {
 		if (currentModel != nullptr)
 		{
 			modelInputAdjustmentDB = currentModel->GetRecommendedInputDBAdjustment();
+
+#ifdef SMART_BYPASS_ENABLED
+			int receptiveFieldSamples = currentModel->GetReceptiveFieldSize();
+
+			if (receptiveFieldSamples > -1)
+			{
+				for (unsigned int i = 0; i < n_samples; i++)
+				{
+					if (abs(ports.audio_in[i]) <= bypassThresholdLinear)
+					{
+						silentSamples++;
+					}
+					else
+					{
+						silentSamples = 0;
+					}
+				}
+
+				if (silentSamples >= (uint32_t)receptiveFieldSamples)
+				{
+					silentSamples = (uint32_t)receptiveFieldSamples;	// Prevent silentSamples growing and eventually overflowing uint32
+
+					if (smartBypassed)
+					{
+						for (unsigned int i = 0; i < n_samples; i++)
+						{
+							ports.audio_out[i] = ports.audio_in[i];
+						}
+
+						return;
+					}
+
+					smartBypassed = true; // If we aren't already, we'll be bypassed on the next process call
+				}
+				else
+					smartBypassed = false;
+			}
+#endif
 		}
 
 		// convert input level from db

src/nam_plugin.h

@@ -60,6 +60,7 @@ namespace NAM {
 			float* audio_out;
 			float* input_level;
 			float* output_level;
+			float* quality_scale;
 		};
 
 		Ports ports = {};
@@ -70,16 +71,19 @@ namespace NAM {
 		LV2_Log_Logger logger = {};
 		LV2_Worker_Schedule* schedule = nullptr;
 
+		NeuralAudio::NeuralModelLoader loader;
 		NeuralAudio::NeuralModel* currentModel = nullptr;
 		std::string currentModelPath;
 		float prevDCInput = 0;
 		float prevDCOutput = 0;
+		float qualityScale = 1.0f;
 
 		Plugin();
 		~Plugin();
 
 		bool initialize(double rate, const LV2_Feature* const* features) noexcept;
 		void set_max_buffer_size(int size) noexcept;
+		void activate() noexcept;
 		void process(uint32_t n_samples) noexcept;
 
 		void write_current_path();
@@ -120,5 +124,8 @@ namespace NAM {
 		float inputLevel = 0;
 		float outputLevel = 0;
 		int32_t maxBufferSize = 512;
+		float bypassThresholdLinear = 0;
+		uint32_t silentSamples = 0;
+		bool smartBypassed = true;
 	};
 }