GQA(Grouped-Query Attention,GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints)是分组查询注意力,GQA将查询头分成G组,每个组共享一个Key 和 Value 矩阵。GQA-G是指具有G组的grouped-query attention。GQA-1具有单个组,因此具有单个Key 和 Value,等效于MQA。而GQA-H具有与头数...
下图能很好的反映Multi-Head/Multi-Query/Grouped-Query Attention之间的区别。 1.Prefill Phase Prefill阶段的计算过程如下,与Multi-Head Attention相比K和V少了一个维度。其实到这边已经也可以预料到Muti-Head Attention在预填充阶段是肯定不会memory bandwidth bound的,但我们这边还是会计算一下。 计算复杂度为Θ(bnd...
transformerspytorchtransformerattentionattention-mechanismsoftmax-layermulti-head-attentionmulti-query-attentiongrouped-query-attentionscale-dot-product-attention UpdatedOct 7, 2023 Python Improve this page Add a description, image, and links to themulti-query-attentiontopic page so that developers can more ...
Multi-head attention consists of multiple attention layers (heads) in parallel with different linear transformations on the queries, keys, values and outputs. Multi-query attention is identical except that the different heads share a single set of keys a
The open source implementation of the multi grouped query attention by the paper "GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints" - kyegomez/MGQA
[76]. The general case, called GLAV, in which queries over the source are mapped to queries over the target, has attracted a lot of attention recently, especially for data exchange. The GAV and LAV are widely implemented in polystores. For more details about query processing via schema ...
与Multi-head Attention相比,Query还是多个头,KV变成一个头,节省了很多计算量。模型的精度会稍微降低一点,但是推理速度会快很多。 Grouped-query Attention是multi-head和multi-query方案的折中。模型精度高于multi-query,速度优于multi-head。LLaMA2在34B和70B的模型上使用了Grouped-Query Attention。
self.hidden_size_per_attention_head))value_layer=value_layer.unsqueeze(-2)value_layer=value_layer...
(Unofficial) PyTorch implementation of grouped-query attention (GQA) from GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints Includes: scaled dot-product attention with GQA support. (See: scaled_dot_product_gqa usage) GQA multi-head attention layer. (See: Multihead...
一般的multi head attention 的qkv的头的数量都一样，而multi query attention的q的头数量保持不变，k...