Build Instructions

macOS

Pre-built binaries are available in the release section of this repo.

• Download the latest libtorch (CPU) here and unzip it to a known directory
• Run the following commands:

git clone https://github.com/acids-ircam/nn_tilde --recursive
cd nn_tilde
mkdir build
cd build
cmake ../src/ -DCMAKE_PREFIX_PATH=/path/to/libtorch -DCMAKE_BUILD_TYPE=Release
make

• Copy the produced .mxo external inside ~/Documents/Max 8/Packages/nn_tilde/externals/

Windows

• Download Libtorch (CPU) and dependencies here and unzip to a known directory.
• Install Visual Studio and the C++ tools
• Run the following commands:

git clone https://github.com/acids-ircam/nn_tilde --recurse-submodules
cd nn_tilde
mkdir build
cd build
cmake . -S ..\src  -DCMAKE_BUILD_TYPE:STRING=Release -G "<generator name of your Visual Studio version>" -A x64  -DTorch_DIR="<unzipped libtorch directory>\share\cmake\Torch"
cmake --build . --config Release

Use cmake --help to find the generator name for your Visual Studio version

• Copy all the DLLs from <unzipped libtorch directory>\lib to the Max 7/8 installation directory, next to Max.exe

Raspberry Pi

While nn~ can be compiled and used on Raspberry Pi, you may have to consider using lighter deep learning models. We currently only support 64bit OS.

Install nn~ for PureData using

curl -s https://raw.githubusercontent.com/acids-ircam/nn_tilde/master/install/raspberrypi.sh | bash