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Utilities for Deep Learning with PyTorch (models, losses, metrics etc.)

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justusschock/dl-utils

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dl-utils: Utilities for Deep Learning with PyTorch

Content

This package contains mainly loss functions, model definitions and metrics in both functional and modular and (whenever possible) pure PyTorch implementations.

Installation

From source

pip install git+https://github.com/justusschock/dl-utils

From PyPi

pip install deep-learning-utils

Subpackages

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 functions
  • dlutils.metrics: implements some common metrics
  • dlutils.models: contains Nd implementations of many popular models
    • dlutils.models.gans: contains many basic gan implementations, but so far not for arbitrary dimensions
  • dlutils.optims: containis additional optimizers
  • dlutils.utils: contains additional utilities such as tensor operations and module loading

Note

  • Most 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