TRAINING.md

Training All-In-One Music Structure Analaysis Models

Install Dependencies

pip install allin1[train]

Setup Weights & Biases

This package uses Weights & Biases to log and track training.

1. Sign up here.
2. Login from terminal:

wandb login

Prepare Data (Harmonix Set)

Make a directory for Harmonix Set:

mkdir -p data/harmonix

You should refer to Harmonix Set and collect the audio files by yourself. Then, place the audio files, metadata, and annotations in the following structure:

data/harmonix
|-- metadata.csv
|-- beats
|   |-- 0001_12step.txt
|   |-- ...
|   `-- 1001_yourloveismydrugdave.txt
|-- segments
|   |-- 0001_12step.txt
|   |-- ...
|   `-- 1001_yourloveismydrugdave.txt
`-- tracks
|   |-- 0001_12step.mp3
|   |-- ...
|   `-- 1001_yourloveismydrugdave.mp3

Preprocess Data

The following command will preprocess the data and save source-separated spectrograms in data/harmonix/features:

allin1-preprocess

Train

The following command will train the model and upload the model and training logs to Weights & Biases:

allin1-train

Then, on your terminal, you will see the link where you can monitor the training:

wandb: 🚀 View run at https://wandb.ai/YOUR_ID/YOUR_PROJECT/runs/xxxxxxxx

You can put options, for example, to specify the fold to train:

allin1-train fold=2

To see all the options, check src/allin1/config.py or run:

allin1-train --help

You can also run multiple training jobs in parallel using Weights & Biases sweep. The example below is a sweep configuration file sweep.yaml for training all folds:

project: all-in-one
program: allin1-train
method: grid
description: >
  Train All-In-One Music Structure Analysis Models for all folds.

metric:
  name: test/loss
  goal: minimize

parameters:
  fold:
    values: [ 0, 1, 2, 3, 4, 5, 6, 7 ]

command:
  - ${env}
  - ${program}
  - ${args_no_hyphens}

You can run the sweep with the following command:

wandb sweep sweep.yaml

And on each GPU, run the following command to start training:

CUDA_VISIBLE_DEVICES=0 wandb agent <SWEEP_ID>
CUDA_VISIBLE_DEVICES=1 wandb agent <SWEEP_ID>
...