What is Skeltorch?

Skeltorch is a light-weight framework that helps researchers to prototype faster using PyTorch. To do so, Skeltorch provides developers with a set of predefined pipelines to organize projects and train/test their models.

Skeltorch is an experiment-based framework. What that means is that every possible variation of your model will be represented by a different experiment. Every experiment is uniquely identified by its name and contains:

  • A set of immutable configuration parameters, specified during its creation.
  • A copy of the data object, also created during the creation of the experiment.
  • The checkpoints of the model associated with the experiment.
  • A set of TensorBoard files with a graphical evolution of the losses and other data that may be logged.
  • A textual log of the actions performed on the experiment.


  • Easy creation and loading of experiments.
  • Automatic restoration of interrupted training.
  • Readable JSON configuration files with the option to validate them using a schema.
  • Visual logging using TensorBoard.
  • Automatic logging using the native Python logging package.
  • Automatic handling of random seeds, specified during the creation of an experiment.
  • Easy implementation of custom pipelines.

Installing Skeltorch

Use pip to install Skeltorch in your virtual environment:

pip install skeltorch