Description:
powerfulbenchmarker 0.9.33
Powerful Benchmarker
Documentation
View the documentation here
Google Colab Examples
See the examples folder for notebooks that show a bit of this library's functionality.
A Metric Learning Reality Check
See supplementary material for the ECCV 2020 paper.
Benchmark results:
4-fold cross validation, test on 2nd-half of classes
Benefits of this library
Highly configurable:
Yaml files for organized configuration
A powerful command line syntax that allows you to merge, override, swap, apply, and delete config options.
Customizable:
Benchmark your own losses, miners, datasets etc. with a simple function call.
Easy hyperparameter optimization:
Append the ~BAYESIAN~ flag to the names of hyperparameters you want to optimize.
Extensive logging:
View experiment data in tensorboard, CSV and SQLite format.
Reproducible:
Config files are saved with each experiment and are easily reproduced.
Trackable changes:
Keep track of changes to an experiment's configuration.
Installation
pip install powerful-benchmarker
Citing the benchmark results
If you'd like to cite the benchmark results, please cite this paper:
@misc{musgrave2020metric,
title={A Metric Learning Reality Check},
author={Kevin Musgrave and Serge Belongie and Ser-Nam Lim},
year={2020},
eprint={2003.08505},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
Citing the code
If you'd like to cite the powerful-benchmarker code, you can use this bibtex:
@misc{Musgrave2019,
author = {Musgrave, Kevin and Lim, Ser-Nam and Belongie, Serge},
title = {Powerful Benchmarker},
year = {2019},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/KevinMusgrave/powerful-benchmarker}},
}
Acknowledgements
Thank you to Ser-Nam Lim at Facebook AI, and my research advisor, Professor Serge Belongie. This project began during my internship at Facebook AI where I received valuable feedback from Ser-Nam, and his team of computer vision and machine learning engineers and research scientists.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
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