REPAIR

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Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair

REPAIR 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# REPAIR: REnormalizing Permuted Activations for Interpolation Repair

![repair](https://raw.githubusercontent.com/KellerJordan/REPAIR/master/figures/relative_twtr2.png)

Code release for [REPAIR: REnormalizing Permuted Activations for Interpolation Repair](https://arxiv.org/abs/2211.08403).

* The notebook [Train-Merge-REPAIR-VGG11](notebooks/Train-Merge-REPAIR-VGG11.ipynb) is a self-contained, PyTorch-only script which trains two standard VGG11 networks on CIFAR-10. It then merges them in weight-space using neuron alignment. Finally, it applies REPAIR to reduce the merging penalty from ~20% to ~5%. The width of the VGG network can be scaled up to obtain zero-barrier connectivity.
* The notebook [Merge-ResNet50-ImageNet](notebooks/Merge-ResNet50-ImageNet.ipynb) applies REPAIR to merging ResNet50s trained on ImageNet. It is less self-contained, depending on [FFCV](https://github.com/libffcv/ffcv) ImageNet files, and two pretrained ResNet50 checkpoints.

These two notebooks contain complete implementations of REPAIR from which further experiments can be derived. The remainder of the notebooks in `./notebooks` contain assorted such experiments.

REPAIR

REPAIR 최신버젼 다운로드

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