TorchLite Plugin

This repo demonstrate how to compile JUCE with libtorch (pytorch C++ library), and run on jitted torch models.

A. Prerequisite

Clone the Repository

$ git clone --recursive https://mastertones@github.com/mastertones/torchGAIN.git

External Libraries

Intel MKL-DNN

Intel MKLDNN (version: 0.20)
Intel MKLML (https://anaconda.org/anaconda/mklml) by anaconda. (NOTE: This issue is temporary solution for installing MKLML.)

B. Compilation

Requirements

cmake
C++ version: 14
JUCE v5.4.5
libtorch v1.3.1

Please arrange all the requirements as the structure of this repo. You can download the backup versions of JUCE and libtorch from here.

Using Xcode

Warning: Xcode failed in building with pytorch. The flags setting is too complicated. If source codes contain torch dependencies, I recommend to use FRUT.

Using FRUT

Install FRUT
- Run install_FRUT.sh
- Remember to set the JUCE path in the script (default: "-DJUCE_ROOT=../../JUCE")
- If failed, check out the orignal repo.

Generate CMakeLists.txt

General Cases
remember to set the path to JUCE modules

$ cd Project
$ ../FRUT/prefix/FRUT/bin/Jucer2Reprojucer deepcore.jucer ../FRUT/prefix/FRUT/cmake/Reprojucer.cmake --juce-modules=<path-to-JUCE-moduls>

Project/CMakeLists.txt has been successfully generated.

With libtroch (optional)
Add the following codes into generated CMakeLists.txt:

# add
set(CMAKE_PREFIX_PATH "../libtorch")
find_package(Torch REQUIRED)

# ...

# modify
jucer_export_target(
    "Xcode (MacOSX)"
    EXTERNAL_LIBRARIES_TO_LINK ${TORCH_LIBRARIES}
    )

Build

$ cd Project
$ mkdir build && cd build/
$ cmake .. -G "Unix Makefiles"
$ cmake --build .

C. Available Effects

Bypass: do nothing
Distortion: hard clipping (0.5) + abs
Gain: multiply 0.01

wayne391/torch-juce-demo