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

@@ -20,7 +20,7 @@ jobs:
       env:
         CXX: clang++
       run: |
-        cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE -DBUILD_UTILS=ON -DBUILD_NAMCORE=ON -DBUILD_STATIC_RTNEURAL=ON 
+        cmake .. -DCMAKE_BUILD_TYPE=$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
 
@@ -51,7 +51,7 @@ jobs:
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
       run: |
-        cmake.exe -G "Visual Studio 17 2022" -A x64 -DBUILD_UTILS=ON -DBUILD_NAMCORE=ON -DBUILD_STATIC_RTNEURAL=ON -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

.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 -DLSTM_PREFER_NAM=OFF -DWAVENET_PREFER_NAM=OFF
+        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 -DLSTM_PREFER_NAM=OFF -DWAVENET_PREFER_NAM=OFF
+        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: ${{github.workspace}}/build
       run: |
-        cmake.exe -G "Visual Studio 17 2022" -A x64  -T ClangCL -DLSTM_PREFER_NAM=OFF -DWAVENET_PREFER_NAM=OFF ..
+        cmake.exe -G "Visual Studio 18 2026" -A x64  -T ClangCL -DUSE_NATIVE_ARCH=${{ 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 -DLSTM_PREFER_NAM=OFF -DWAVENET_PREFER_NAM=OFF -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 0.1.7)
+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

@@ -1,7 +1,11 @@
+[GitHub contributers](https://github.com/mikeoliphant/neural-amp-modeler-lv2/graphs/contributors)
+
 This repository uses code from a number of sources. Please see them for code licensing information:
 
 https://github.com/mikeoliphant/NeuralAudio
 
 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

@@ -1,27 +1,33 @@
 # 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 plenty of room to spare for a cabinet IR and some effects. It is also capable of running two "standard" NAM models, but with less headroom for other 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
 
@@ -57,4 +63,6 @@ After building, the plugin will be in **build/neural_amp_modeler.lv2**.
 
 ```-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.
 
+```-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

@@ -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 ()
 
@@ -48,6 +54,15 @@ if (DISABLE_DENORMALS)
 	add_definitions(-DDISABLE_DENORMALS)
 endif (DISABLE_DENORMALS)
 
+option(SMART_BYPASS_ENABLED "Enable auto-bypass on silence" OFF)
+
+if (SMART_BYPASS_ENABLED)
+	add_definitions(-DSMART_BYPASS_ENABLED)
+	message(STATUS "Smart Bypass enabled")
+else()
+	message(STATUS "Smart Bypass NOT enabled")
+endif (SMART_BYPASS_ENABLED)
+
 set_target_properties(neural_amp_modeler
 	PROPERTIES
 	CXX_VISIBILITY_PRESET hidden

src/nam_plugin.cpp

@@ -7,12 +7,18 @@
 
 #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);
 
+		bypassThresholdLinear = powf(10, BYPASS_DB_THRESHOLD * 0.05f);
+
 //		NeuralAudio::NeuralModel::SetLSTMLoadMode(
 //#ifdef LSTM_PREFER_NAM
 //			NeuralAudio::PreferNAMCore
@@ -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;
 	};
 }