Metadata-Version: 2.1
Name: declair
Version: 0.1.2
Summary: Package for declarative hyperparameter search experiments.
Home-page: https://gitlab.com/k-cybulski/declair
Author: Krzysztof Cybulski
Author-email: declair@kcyb.eu
License: EUPL-1.2-or-later
Description: # Declair :cake:
        [![pipeline status](https://gitlab.com/k-cybulski/declair/badges/master/pipeline.svg)](https://gitlab.com/k-cybulski/declair/-/commits/master)
        [![coverage report](https://gitlab.com/k-cybulski/declair/badges/master/coverage.svg)](https://gitlab.com/k-cybulski/declair/-/commits/master)
        
        Declair is a framework for declaratively defining hyperparameter optimization experiments. It uses [Sacred](https://github.com/IDSIA/sacred) for storing experiment results and supports [hyperopt](https://github.com/hyperopt/hyperopt) for optimization.
        
        It came about from attempts to recreate DeepSolaris results in PyTorch instead of Keras. However, it grew to be a more extensive and general framework than originally planned.
        
        # Usage
        For detailed instructions on how to use Declair, see the [documentation](https://k-cybulski.gitlab.io/declair/).
        
        ## Installation
        Install required Python packages in your favourite virtual environment
        ```
        pip install -r requirements.txt
        ```
        
        ## Running the tests
        Go into the root of the repository (i.e. where this README.md is) and run 
        ```
        python -m pytest
        ```
        
        # Credits
        This project has been heavily inspired by [cbds_common](https://gitlab.com/CBDS/cbds_common).
        
Platform: UNKNOWN
Requires-Python: >=3.5
Description-Content-Type: text/markdown
