位置逐元素前馈(position-wise feed-forward)在Transformer架构中被广泛使用,可以放在自注意力(self-attention)层之后,它的主要目的是在每个序列的位置单独应用一个全连接前馈网络。 自注意力子层用于捕捉序列中的长距离依赖关系,而位置逐元素前馈子层则用于学习局部特征,二者可以配合使用。例如,在GPT(基于Transformer的解...
3.3 搭建Position Wise Feed Forward 我们在__init__方法中就已经获取了全部的所需函数,所以,接下来直接搭建Forward即可! def forward(self, x): x = self.linear1(x) x = self.relu(x) x = self.dropout(x) x = self.linear2(x) return x 到这里一个Position Wise Feed Forward就ok了~ 4. Q&A...
In this paper, we propose the first hardware accelerator for two key components, i.e., the multi-head attention (MHA) ResBlock and the position-wise feed-forward network (FFN) ResBlock, which are the two most complex layers in the Transformer. Firstly, an efficient method is introduced to...