A PyTorch toolkit for audio synthesis.
Project description
Audyn
Audyn is PyTorch toolkit for audio synthesis.
Build Status
Installation
You can install by pip.
pip install Audyn
# from source
# pip install git+https://github.com/tky823/Audyn.git
or clone this repository.
git clone https://github.com/tky823/Audyn.git
cd Audyn
pip install -e .
If you need to run recipes, add [recipes] as follows:
# In Audyn/
pip install -e ".[recipes]"
If you use MacOS, you may need to set MACOSX_DEPLOYMENT_TARGET during installation to build C++ related modules.
C++ extension
We use C++ extension to search monotonic alignment in some models (e.g. GlowTTS).
To take full advantage of computational efficiency, set appropriate value of OMP_NUM_THREADS and CXX during installation:
# In Audyn/
export CXX=<PATH/TO/CPP/COMPILER> # e.g. /usr/bin/c++
export OMP_NUM_THREADS=<SUITABLE/VALUE/FOR/ENVIRONMENT>
pip install -e "."
Backend of torchaudio
For torch>=2.9, torchcodec is required as backend of torchaudio:
pip install torchcodec
Development
git clone https://github.com/tky823/Audyn.git
cd Audyn
pip install -e ".[recipes,dev,tests]"
Build Documentation Locally (optional)
To build the documentation locally, you have to include docs when installing Audyn.
pip install -e ".[docs]"
When you build the documentation, run the following command.
cd docs/
make html
Or, you can build the documentation automatically using sphinx-autobuild.
# in Audyn/
sphinx-autobuild docs docs/_build/html
Test
pytest tests/package
To include DDP tests
pytest tests/package --runddp
To include slow tests
pytest tests/package --runslow
License
- Apache License, Version 2.0 EXCEPT FOR WEIGHTS OF PRETRAINED MODELS
- Weights for some of the pre-trained models are extracted from the official implementations. Their licenses follow the official implementations.
Project details
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