pytorch_lightning_wavenet

A PytorchLightning implementation of mel-spectrogram vocoder using WaveNet. Created with reference to Chainer implementation.

Usage

1. Bulid Docker image.
   • sudo docker build -t pytorch_lightning_wavenet .
2. Run Docker container.
   • sudo docker run --shm-size=512m --gpus all --rm -v $PWD/wavenet:/wavenet -w /wavenet -it pytorch_lightning_wavenet:latest bash
3. Download dataset.
   • wget http://www.udialogue.org/download/VCTK-Corpus.tar.gz
   • tar -xf VCTK-Corpus.tar.gz
4. Start training.
   • python train.py --dataset <directory of dataset e.g. ./VCTK-Corpus/>
5. Generate audio with trained model.
   • python generate.py -i <input file> -m <trained model e.g. ./lightning_logs/version_0/checkpoints/last.ckpt>