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[ICLR2023] How I Learned to Stop Worrying and Love Retraining\n*Authors: [Max Zimmer](https://maxzimmer.org/), [Christoph Spiegel](http://www.christophspiegel.berlin/), [Sebastian Pokutta](http://www.pokutta.com/)*\n\nThis repository contains the code to reproduce the experiments from the ICLR2023 paper [\"How I Learned to Stop Worrying and Love Retraining\"](https://arxiv.org/abs/2111.00843).\nThe code is based on [PyTorch 1.9](https://pytorch.org/) and the experiment-tracking platform [Weights \u0026 Biases](https://wandb.ai). \nThe code to reproduce semantic segmentation as well as NLP experiments will be added soon.\n\n\n### Structure and Usage\nExperiments are started from the following file:\n- [`main.py`](main.py): Starts experiments using the dictionary format of Weights \u0026 Biases.\n\nThe rest of the project is structured as follows:\n- [`strategies`](strategies): Contains all used sparsification methods.\n- [`runners`](runners): Contains classes to control the training and collection of metrics.\n- [`metrics`](metrics): Contains all metrics as well as FLOP computation methods.\n- [`models`](models): Contains all model architectures used.\n- [`utilities`](models): Contains useful auxiliary functions and classes.\n\n\n### Citation\nIn case you find the paper or the implementation useful for your own research, please consider citing:\n\n```\n@inproceedings{zimmer2023how,\ntitle={How I Learned to Stop Worrying and Love Retraining},\nauthor={Max Zimmer and Christoph Spiegel and Sebastian Pokutta},\nbooktitle={The Eleventh International Conference on Learning Representations },\nyear={2023},\nurl={https://openreview.net/forum?id=_nF5imFKQI}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzib-iol%2Fbimp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzib-iol%2Fbimp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzib-iol%2Fbimp/lists"}