seqcode/WaveNet

Yet another WaveNet implementation in PyTorch.

Python

WaveNet

Yet another WaveNet implementation in PyTorch.

The purpose of this implementation is Well-structured, reusable and easily understandable.

Prerequisites

System
- Linux or macOS
- CPU or (NVIDIA GPU + CUDA CuDNN)
  - It can run on Single CPU/GPU or Multi GPUs.
- Python 3
Libraries
- PyTorch >= 0.3.0
- librosa >= 0.5.1

Training

python train.py \
    --data_dir=./test/data \
    --output_dir=./outputs

Use python train.py --help to see more options.

Generating

It's just for testing. You need to modify for real world.

python generate.py \
    --model=./outputs/model \
    --seed=./test/data/helloworld.wav \
    --out=./output/helloworld.wav

Use python generate.py --help to see more options.

File structures

networks.py and model.py is main implementations.

wavenet
- config.py : Training options
- networks.py : The neural network architecture of WaveNet
- model.py : Calculate loss and optimizing
- utils
  - data.py : Utilities for loading data
- test
  - Some tests for check if it's correct model like casual, dilated..
train.py : A script for WaveNet training
generate.py : A script for generating with pre-trained model

TODO

References