Online normalizer calculation for softmaxarxiv.org/abs/1805.02867 首先回顾一下Self-Attention的计算: O=sofmax(QKT)V 其中,Q,K,V,均可表示为形状为(N,D)的二维矩阵,其中N为输入序列的长度,D为特征维度。softmax可以分解为以下3个步骤: S=QKT∈RN×NP=softmax(S)∈RN×NO=PV∈RN×D 注意:S和O...
Online normalizer calculation for softmax FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness From Online Softmax to FlashAttention 拓展阅读 Flash Attention V1/V2 forward 本文涉及的代码也上传github 《手撕RLHF》 解析如何系统的来做LLM对齐工程 小冬瓜AIGC:【手撕RLHF-DPO】step-...
Online normalizer calculation for softmax 来自 arXiv.org 喜欢 0 阅读量: 159 作者:M Milakov,N Gimelshein 摘要: The Softmax function is ubiquitous in machine learning, multiple previous works suggested faster alternatives for it. In this paper we propose a way to compute classical Softmax with...
@@ -64,6 +72,33 @@ void softmax_forward_cpu(float* out, float* inp, int N, int C) { } } // online version of softmax on CPU from the paper "Online normalizer calculation for softmax" void softmax_forward_online_cpu(float* out, float* inp, int N, int C) { // inp is ...
[2]Andrew Kerr. Gtc 2020: developing cuda kernels to push tensor cores to the absolute limit on nvidia a100. May 2020. [3]Maxim Milakov and Natalia Gimelshein. Online normalizer calculation for softmax.CoRR, abs/1805.02867, 2018.