Bottleneck transformer
时间: 2023-08-27 11:07:21 浏览: 138
Bottleneck Transformer是一种深度学习模型,它是在ViT(Vision Transformer)中引入的一种变体。它通过在Multi-Head Self-Attention结构前后加上1×1卷积层来构建。Bottleneck Transformer和ViT中的Transformer block具有亲属关系,它们的结构并不完全不同。作者在论文中指出,具有MHSA的ResNet bottleneck块可以被视为具有bottleneck结构的Transformer块,除了一些细微的差异,如残差连接和规范化层的选择等。Bottleneck Transformer模型在2021年由Google的研究人员在论文"Bottleneck Transformers for Visual Recognition"中提出。
如果你想使用Bottleneck Transformer模型,你可以通过pip命令安装bottleneck-transformer-pytorch库,并按照提供的用法进行引用和使用。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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- *1* [深度学习之图像分类(十九)-- Bottleneck Transformer(BoTNet)网络详解](https://blog.csdn.net/baidu_36913330/article/details/120218954)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 33.333333333333336%"]
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- *3* [bottleneck-transformer-pytorch:Pytorch中瓶颈变压器的实现](https://download.csdn.net/download/weixin_42111465/15605077)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 33.333333333333336%"]
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