From a6f0bebd1a8b268ff1c4e46b4d34a2af194ea16e Mon Sep 17 00:00:00 2001
From: Hugo Touvron <49280617+TouvronHugo@users.noreply.github.com>
Date: Wed, 29 Dec 2021 12:06:14 +0100
Subject: [PATCH] Create README_patchconvnet.md

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+# Augmenting Convolutional networks with attention-based aggregation
+
+This repository contains PyTorch evaluation code, training code and pretrained models for the following projects:
+* [DeiT](README.md) (Data-Efficient Image Transformers), ICML 2021 
+* [CaiT](README_cait.md) (Going deeper with Image Transformers), ICCV 2021 (Oral)
+* [ResMLP](README_resmlp.md) (ResMLP: Feedforward networks for image classification with data-efficient training)
+* PatchConvnet (Augmenting Convolutional networks with attention-based aggregation)
+
+PatchConvnet allows to have interpretable attention maps with convnets:
+
+<p align="center">
+  <img width="900"  src=".github/patch_convnet.png">
+</p>
+
+For details see [Augmenting Convolutional networks with attention-based aggregation](https://arxiv.org/abs/2112.13692) by Hugo Touvron, Matthieu Cord, Alaaeldin El-Nouby, Matthieu Cord, Piotr Bojanowski, Armand Joulin, Gabriel Synnaeve and Hervé Jégou.
+
+If you use this code for a paper please cite:
+
+```
+@article{touvron2021patchconvnet,
+  title={Augmenting Convolutional networks with attention-based aggregation},
+  author={Hugo Touvron and Matthieu Cord and Alaaeldin El-Nouby and Piotr Bojanowski and Armand Joulin and Gabriel Synnaeve and Jakob Verbeek and Herv'e J'egou},
+  journal={arXiv preprint arXiv:2112.13692},
+  year={2021},
+}
+```
+
+# Model Zoo
+
+We provide PatchConvnet models pretrained on ImageNet-1k 2012:
+
+| name | acc@1 | res | FLOPs| #params | url |
+| --- | --- | --- | --- | --- | --- | 
+| S60 | 82.1 | 224 |4.0B| 25.2M| coming soon |
+| S120| 83.2 | 224 |  7.5B |47.7M | coming soon |
+| B60 | 83.5 | 224 |  15.8B |99.4M | coming soon |
+| B120 |84.1 | 224 |  29.9B |188.6M | coming soon |
+
+Model pretrained on ImageNet-21k with finetuning on ImageNet-1k 2012:
+
+| name | acc@1 | res | FLOPs| #params | url |
+| --- | --- | --- | --- | --- | --- | 
+| S60 |83.5 | 224 |  4.0B |25.2M |coming soon |
+| S60 |84.9 | 384 |  11.8B |25.2M |coming soon |
+| S60 |85.4 | 512 |  20.9B |25.2M |coming soon |
+| B60 |85.4 | 224 |  15.8B |99.4M |coming soon |
+| B60 |86.5 | 384 |  46.5B |99.4M |coming soon |
+| B120 |86.0 | 224 |  29.8B |188.6M |coming soon |
+| B120 |86.9 | 384 |  87.7B |188.6M |coming soon |
+
+The models are also available via torch hub.
+Before using it, make sure you have the latest pytorch-image-models package [`timm`](https://github.com/rwightman/pytorch-image-models) by [Ross Wightman](https://github.com/rwightman) installed. 
+
+
+# License
+This repository is released under the Apache 2.0 license as found in the [LICENSE](LICENSE) file.
+
+# Contributing
+We actively welcome your pull requests! Please see [CONTRIBUTING.md](.github/CONTRIBUTING.md) and [CODE_OF_CONDUCT.md](.github/CODE_OF_CONDUCT.md) for more info.