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- GitHub - SHI-Labs NATTEN: Neighborhood Attention Extension. Bringing . . .
NATTEN is an open-source project dedicated to providing infrastructure for Neighborhood Attention (NA), a sliding window self-attention mechanism, and its extensions (dilated NA, causal NA, strided NA)
- 【Bug】natten：安装报错（临近注意力机制的高效cuda内核实现）_natten库-CSDN博客
NATTEN(Neighborhood Attention Extension)是一个为PyTorch提供快速滑动窗口注意力机制实现的开源项目。它的核心是邻域注意力(Neighborhood Attention),这是一种局部化的自注意力机制,可以在保持高效计算的同时捕获图像的局部上下文信息。
- Install - NATTEN
Install NATTEN Starting version 0 20 0, NATTEN only supports PyTorch 2 7 and newer However, you can still attempt to install NATTEN with PyTorch >= 2 5 at your own risk For earlier NATTEN releases, please refer to Older NATTEN builds We strongly recommend NVIDIA GPU users to install NATTEN with our CUDA kernel library, libnatten
- Neighborhood Attention Transformer - 知乎 - 知乎专栏
本文提出了Neighborhood Attention Transformer(NAT)，NAT是一种集高效、准确和可扩展的分层Transformer，Neighborhood Attention是一种简单而灵活的 Self Attention 机制，它将每个query的感受野扩展到其最近的邻近像素，并随着感受野的增大而接近Self-Attention。 NAT-Tiny在ImageNet上达到83 2%的Top-1精度，只有4 3 GFLOPs和28M参数
- natten·PyPI
NATTEN is an open-source project dedicated to providing infrastructure for Neighborhood Attention (NA), a sliding window self-attention mechanism, and its extensions (dilated NA, causal NA, strided NA)
- NATTEN - 高效实现多维滑动窗口自注意力的开源库 - 懂AI
NATTEN是一个开源库，专门用于快速实现Neighborhood Attention。该项目支持1D、2D和3D问题空间，提供naive、GEMM以及新型Fused Neighborhood Attention (FNA)等多种后端实现。FNA引入反向传播支持，显著提高了模型训练效率。
- Releases · SHI-Labs NATTEN - GitHub
Neighborhood Attention Extension Bringing attention to a neighborhood near you! - SHI-Labs NATTEN
- [2204. 07143] Neighborhood Attention Transformer - arXiv. org
We develop NATTEN (Neighborhood Attention Extension), a Python package with efficient C++ and CUDA kernels, which allows NA to run up to 40% faster than Swin's WSA while using up to 25% less memory We further present Neighborhood Attention Transformer (NAT), a new hierarchical transformer design based on NA that boosts image classification and
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