GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.
Thanks to the non-invasive nature of the framework, it is easy to add another new architectures beside ResNet. All you need is to paste your model code into themodelfolder, and then add a corresponding entry in themodel/model.py. The quantization framework will automatically replace layers sp...
小小神兽发表于机器学习漫... 量化笔记 | 生成对抗量化的ZAQ 有童心的老王 大模型量化之 GPTQ方法 背景知识Layer-Wise Quantization通过逐层量化,目的是找到一个量化权重 \hat W,使量化损失最小。 argmin_{\hat W}||WX-\hat WX||_2^2 ,其中 X 为层输入。想要知道 GPTQ 算法原理,先要了… Jeff打开...
论文链接:https://arxiv.org/abs/1902.08153 源码链接(非官方复现):https://github.com/zhutmost/lsq-net 摘要 在推理时以低精度操作运行的深度网络比高精度具有功耗和存储优势,但需要克服随着精度降低而保持高精度的挑战。在这里,本文提出了一种训练此类网络的方法,即 Learned Step Size Quantization,当使用来自各...
https://github.com/una-dinosauria/local-search-quantization 4. https://github.com/hellozting/CompositeQuantization References Download references Acknowledgements We thank NVIDIA for the donation of GPUs used in this project. Shobhit was supported by a Mitacs Globalink research internship while at UBC...
期待大家继续支持和关注Adlik的Github仓库。 参考文献: [1]developer.nvidia.com/bl [2]Zhewei Yao, Zhen Dong et al., HAWQV3: Dyadic Neural Network Quantization. arXiv:2011.10680 [cs.CV], 2020.11 [3]Yuhang Li, Ruihao Gong et al., BRECQ: Pushing the Limit of Post-Training Quantization by ...
LSQ+: Improving low-bit quantization through learnable offsets and better initializationn解读 与ReLU不同,在流行的高效架构中经常使用的较新的激活函数(如Swish、H-swish、Mish)也可能产生负激活值,其正负取值范围是不对称 量化 初始化 激活函数 权重 原创 bug404 1月前 50阅读 数学公式的规约(reduce)...
Paper地址:https://arxiv.org/abs/1902.08153 GitHub地址 (PyTorch):https://github.com/zhutmost/lsq-net 基本量化设置 计算结点伪量化: Weight跟Activation都采用Per-tensor量化; Scaling factor (Paper标记为Step size)是可学习参数; 量化计算公式: Step... 查看原文 LSQ+: Improving low-bit quantization ...
Weight Quantization and Encoding 本文涉及了DNN中采用的均匀权重量化方案,研究了下图中权重量化与编码的过程。 背景:Tensor-RT解决方案(FP32完全可以降低为INT8推理,量化目的为在精度几乎持平的情况下,很大程度上提升推理速度) Tensor-RT有关内容见:https://arleyzhang.github.io/articles/923e2c40/ 本文将对上述图...
LSQ+: Improving low-bit quantization through learnable offsets and better initialization https://github.com/666DZY666/micronet https://github.com/hustzxd/LSQuantization https://github.com/zhutmost/lsq-net https://github.com/Zhen-Dong/HAWQ ...