KUIELab-MDX-Net¶
0. Environment¶
Ubuntu 20.04
at least four cuda-able GPUs (each >= 2080ti)
1.5 TB disk storage for data augmentation
wandb for logging
Also, you must create .env file by copying .env.sample to set environmental variables.
wandb_api_key=[Your Key] # "xxxxxxxxxxxxxxxxxxxxxxxx"
data_dir=[Your Path] # "/home/ielab/repos/musdbHQ"
about
wandb_api_keywe currently only support wandb for logging.
for
wandb_api_key, visit wandb, go tosetting, and then copy your api key
about
data_dirthe absolute path where datasets are stored
1. Installation¶
conda env create -f conda_env_gpu.yaml -n mdx-net
conda activate mdx-net
pip install -r requirements.txt
sudo apt-get install soundstretch
2. Training & Submission¶
3. Leaderboard A vs Leaderboard B¶
The main difference between the branch Leaderboard_A and Leaderboard_B is the usage of the test dataset of Musdb18.
Leaderboard A does not use test dataset for training: https://github.com/kuielab/mdx-net/blob/Leaderboard_A/configs/experiment/multigpu_default.yaml
Leaderboard B uses test dataset for training: https://github.com/kuielab/mdx-net/blob/b45eff172928dc9fc31852ee65072fb01f4c2d08/configs/experiment/multigpu_default.yaml#L16
ACKNOWLEDGEMENT¶
This repository is based on Lightning-Hydra Template
Repository of TFC-TDF-U-Net, our previous ISMIR 2020 paper
Also, facebook/demucs