confugue 0.0.1

Hierarchical configuration framework

confugue is a hierarchical configuration framework for Python. It provides a wrapper class for nested configuration dictionaries (usually loaded from YAML files), which can be used to configure complicated object hierarchies in a recursive fashion.

As an example, here is a simplified code snippet from a machine learning project which uses confugue:

@configurable
class Model:

    def __init__(self, vocabulary, use_sampling=False):
        self.embeddings = self._cfg['embedding_layer'].configure(EmbeddingLayer,
                                                                 input_size=len(vocabulary))
        self.decoder = self._cfg['decoder'].configure(RNNDecoder,
                                                      vocabulary=vocabulary,
                                                      embedding_layer=self.embeddings)

@configurable
class RNNDecoder:

    def __init__(self, vocabulary, embedding_layer):
        self.cell = self._cfg['cell'].configure(tf.keras.layers.GRUCell,
                                                units=100,
                                                dtype=tf.float32)
        self.output_projection = self._cfg['output_projection'].configure(
            tf.layers.Dense,
            units=len(vocabulary),
            use_bias=False)

The model could then be configured using the following config file, overriding the values specified in the code and filling in the ones that are missing.

embedding_layer:
  output_size: 300
decoder:
  cell:
    class: !!python/name:tensorflow.keras.layers.LSTMCell
    units: 1024
use_sampling: True

Installation & Documentation

A full documentation can be found here.

The package is available from PyPI and can be installed with pip install confugue.