Metadata-Version: 2.1
Name: deep-learning-utils
Version: 0.0.1rc3
Summary: UNKNOWN
Home-page: UNKNOWN
Author: Justus Schock
Maintainer: Justus Schock
Maintainer-email: justus.schock@rwth-aachen.de
License: MIT
Description: # 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](https://github.com/PyTorchLightning/pytorch-lightning)) or in your custom training loops
        
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
