但是在Attention中会对他们三个区别对待,将其分别称为Key 、Quary、Value Query,Key,Value的概念取自于信息检索系统,举个简单的搜索的例子来说。当你在某电商平台搜索某件商品(篮球)时,你在搜索引擎上输入的内容便是Query,然后搜索引擎根据Query为你匹配Key(例如商品的种类,颜色,描述等),然后根据Query和Key的相似...
输出就是 value 的加权和,value 的权重由 query 和 value 对应的 key 通过一个兼容性函数(在论文中是按元素乘积再求和,即向量的点积,我们将在后面默认按照这种计算方式)计算得到的。对于上面的例子,我们为"holding"计算一个 query,一个 key-value 对,同时其他的单词也各自计算他们的一个 query 和一个 key-val...
Key:A key is a label of a word and is used to distinguish between different words. Query:Check all available keys and selects the one, that matches best. So it represents an active request for specific information. Value:Key and values always come in pairs. When a query matches a key,...
We’ve just explained the most important equation for Transformer, the underlying architecture of GPT: Q is Query; K is Key; V is Value. Source: Attention is All You Need Advanced notes: 1. Each alchemist looks at every bottle, including their own [Q·K.tr...
注意力分数:query与key的相似度;注意力权重:对以上分数做softmax之后的结果。将变量拓展到高维向量,便得到了 注意力池化层。参数化参数化的注意力机制,例如增加一个 可学习的 w。在上图中,也就是“如何设计a函数(Attention scoring function)的问题”。
Attention Is All You Need のQuery, Key, Valueは、Query, Query, Queryぐらいの解釈でも問題ない(と思う。)以下は、余興。 BERTと、論文『Attention Is All You Need』に対する読解力を、競ってみた(全20問)。くどいですが、以下なども関連記事。 論文『Attention is all you need』を読み間違...
emm报道好像出了一点点偏差,其实attention的定义要general很多,这个query key value只是通常用于self-attention的计算。nlp领域可以说attention is all you need,vision可不行 2021-04-19 09:486回复 temp_name_fang补充一下,vision也可以了,2020还是paper看少了 2021-04-27 01:531回复 GBA1B回覆@temp_name_fan...
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention Aniruddha Nrusimha, Rameswar Panda, Mayank Mishra, William Brandon, Jonathan Ragan Kelly 21 May 2024 139 MLKV: Multi-Layer Key-Value Heads for Memory Efficient Transformer Decoding ...
Query, Key, Value 实际上是三个独立的线性层。每个线性层都有自己独立的权重。输入数据与三个线性层...
supply context for it. Those keys are related to values that encode more meaning about the key word. Any given word can have multiple meanings and relate to other words in different ways, you can have more than one query-key-value complex attached to it. That’s “multi-headed attention....