YAMLHParams

A small extension to the ruamel.yaml CommentedMap YAML parser class (see https://yaml.readthedocs.io/en/latest/). This extension enables access to and manipulation of hyperparameters stored in YAML files using hierarchical/path-like (/path/to/value) lookups of attributes and may perform simple version controlling against a separate Python package and its parent folder git repository. Changes made to the hyperparameters in memory can be easily written to disk preserving comments and order of YAML blocks.

The intended usage is for e.g. machine learning research projects for maintaining a consistent set of hyperparameters on-disk and in-memory while keeping track of the software version used to run a given set of experiments.

Installation

pip install yamlhparams

Examples

Given a file hyperparameters.yaml with content:

fit:
  n_epochs: 100
  loss_function:  # Some comment
    class: cross_entropy
    kwargs:
      class_weights: [1.5, 0.4, 2.0]
  optimizer:
    learning_rate: 1e-5

logging:
  path: /my/path
  level: WARNING

Loading and accessing hyperparameters using typical dictionary lookup or hierarchical /path/to/value styles and performing version control against a 3rd party package my_ml_package:

from yamlhparams import YAMLHParams
hparams = YAMLHParams('hyperparameters.yaml', 
                      version_control_package_name='my_ml_package')
print(hparams['logging']['level'])
>> WARNING

print(hparams.get_group('/fit/loss_function/class'))
>> cross_entropy

print(hparams.get_group('/fit/optimizer'))
>> ordereddict([('learning_rate', 1e-05)])

Adding/deleting groups to/from the hyperparameter file:

hparams.set_group('/data/splits', {'train_inds':[1, 4, 6], 
                                   'test_inds': [2, 3, 5]}, 
                  missing_parents_ok=True)

hparams.delete_group('/logging')

# Save changes to file, preserving comments and order
hparams.save_current()

The modified file now has the following content:

__package_info__:
  package: my_ml_package
  version: 0.1.0
  git:
    commit: 31dd454
    branch: main

fit:
  n_epochs: 100
  loss_function:  # Some comment
    class: cross_entropy
    kwargs:
      class_weights: [1.5, 0.4, 2.0]
  optimizer:
    learning_rate: 1e-5

data:
  splits:
    train_inds:
    - 1
    - 4
    - 6
    test_inds:
    - 2
    - 3
    - 5

Loading the same hyperparameter file with the installed my_ml_package later updated to version 0.2.0 will raise a RuntimeWarning:

[...]
RuntimeWarning: Parameter file indicates that this project was created under 
                my_ml_packagae version 0.1.0, but the current version is 0.2.0. 
                If you wish to continue using this software version on this project dir, 
                manually update to the following lines in the hyperparameter file:

__package_info__:
  version: 0.2.0