Utilities for Deep Learning with PyTorch (models, losses, metrics etc.)
MIT License
This package contains mainly loss functions, model definitions and metrics in both functional and modular and (whenever possible) pure PyTorch implementations.
pip install git+https://github.com/justusschock/dl-utils
pip install deep-learning-utils
Currently there are the following subpackages:
dlutils.data
: contains data utilities (so far just a dataset for random fake data)dlutils.losses
: extends the losses given in PyTorch itself by a few more loss functionsdlutils.metrics
: implements some common metricsdlutils.models
: contains Nd implementations of many popular models
dlutils.models.gans
: contains many basic gan implementations, but so far not for arbitrary dimensionsdlutils.optims
: containis additional optimizersdlutils.utils
: contains additional utilities such as tensor operations and module loadingMost of this code was only tested sparely and not with a proper CI/CD and unittests. I'm currently working on that and any contributions are highly welcomed.
All implementations are done for pure PyTorch. You can employ them in whatever training framework you want (like [pytorch/ignite]{https://github.com/pytorch/ignite) or Pytorch-Lightning) or in your custom training loops