kaizo 0.1.0

A modular YML config file parser and runner.

Kaizo

YML file config reader and runner

The parser in utils/parser.py makes experiments highly flexible. Each YAML file may contain:

• Direct values: simple scalars (e.g., epochs: 10)
• Resolvable values: dictionaries specifying module, source, call, args, and optional lazy
• References: re-use values defined earlier in the config (args.variable_name)
• Local modules: custom Python files specified by local to extend functionality

This design lets you declaratively define entire experiments.

Example Config

Below is the example config file:

ddpm:
  module: trainer.models.ddpm
  source: DDPMTrainer
  args:
    prefix: notebooks
    model_type: sde
    img_size: 32
    in_channels: 1
    batch_size: 64
    shuffle: True
    save_freq: 50
    dataset_path: ./notebooks/data
    beta_min: 0.1
    beta_max: 1
    target_transform:
    download: True
    loader:
      module: loaders
      source: MNISTLoader
      call: False

This config demonstrates:

• Loading MNIST with MNISTLoader
• Using an SDE-based diffusion trainer
• Training with batch_size=64 and saving checkpoints every 50 steps
• Building a UNet-like model with in_channels=1 and img_size=32