Use gcc15 for linux builds

.github/workflows/build.yml

@@ -14,11 +14,17 @@ jobs:
     - uses: actions/checkout@v3.3.0
       with:
         submodules: recursive
+
+    - name: Setup GCC 15
+      uses: egor-tensin/setup-gcc@v2
+      with:
+        version: '15'
     
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
       env:
-        CXX: clang++
+        CXX: g++-15
+        CXXFLAGS: "-static-libstdc++ -static-libgcc"              
       run: |
         cmake .. -DCMAKE_BUILD_TYPE=$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

.github/workflows/release.yml

@@ -41,11 +41,17 @@ jobs:
     - uses: actions/checkout@v3.3.0
       with:
         submodules: recursive
+
+    - name: Setup GCC 15
+      uses: egor-tensin/setup-gcc@v2
+      with:
+        version: '15'
     
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
       env:
-        CXX: clang++
+        CXX: g++-15
+        CXXFLAGS: "-static-libstdc++ -static-libgcc"
       run: |
         cmake .. -DCMAKE_BUILD_TYPE=$BUILD_TYPE -DUSE_NATIVE_ARCH=${{ matrix.native_arch }} -DBUILD_NAMCORE=ON -DBUILD_INTERNAL_STATIC_WAVENET=ON -DBUILD_INTERNAL_STATIC_LSTM=ON
         cmake --build . --config $BUILD_TYPE -j4
@@ -72,7 +78,7 @@ jobs:
         native_arch: [rpi4, rpi5]
     runs-on: ubuntu-latest
     container: 
-      image: ghcr.io/tttapa/docker-arm-cross-toolchain:aarch64-rpi3-linux-gnu-gcc12
+      image: ghcr.io/tttapa/docker-arm-cross-toolchain:aarch64-rpi3-linux-gnu-gcc15
     env:
       ARCHIVE_NAME: neural_amp_modeler_lv2_${{ matrix.native_arch }}.tgz
     steps:
@@ -82,6 +88,8 @@ jobs:
     
     - name: Build Plugin
       working-directory: ${{github.workspace}}/build
+      env:
+        CXXFLAGS: "-static-libstdc++ -static-libgcc"
       run: |
         cmake .. -DCMAKE_BUILD_TYPE=$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

CMakeLists.txt

@@ -1,6 +1,6 @@
 cmake_minimum_required(VERSION 3.10)
 
-project(NeuralAmpModelerLv2 VERSION 0.2.0)
+project(NeuralAmpModelerLv2 VERSION 0.2.1)
 
 set(CMAKE_MODULE_PATH "${CMAKE_SOURCE_DIR}/cmake")
 set(LIB_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib CACHE PATH "The library install dir (default: lib)")

README.md

@@ -5,7 +5,7 @@ LV2 plugin for neural network machine learning amp model playback using the [Neu
 **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/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.
+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. An exception to this is oversampling (running at an even multiple of the model sample rate). See the "[Oversampling](https://github.com/mikeoliphant/neural-amp-modeler-lv2/blob/main/README.md#oversampling)" section below.
 
 For amp-only models (the most typical), **you will need to run an impulse reponse after this plugin** to model the cabinet.
 
@@ -33,6 +33,10 @@ For more information on model type support and performance, see the [NeuralAudio
 
 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.
 
+## Oversampling
+
+If you run at a sample rate that is an even multiple of the model sample rate, the model will be correctly oversampled to behave as expected. So, if the model sample rate is 48kHz (which they typically are), and you are running at 96kHz, the model will be 2x oversampled. This also means that if your DAW supports oversampling, you can safely use it. Running oversampled comes with a signficant performance cost, but can be useful for reducing aliasing.
+
 ## Building
 
 First clone the repository: