We employ multi-headed self-attention (MHSA) while integrating an important technique from Transformer-XL [20],the relative sinusoidal positional encoding scheme. The relative positional encoding allows the self-attention module to generalize better on different input length and the resulting encoder is...
为什么不用学得参数而采用sinusoid函数呢?sinusoidal函数并不受限于序列长度,其可以在遇到训练集中未出现过的序列长度时仍能很好的“extrapolate.” (外推),这体现了其具有一些inductive bias。对于2,shaw et al.2018中的相对位置编码Tensor是两个需要参数学习的tensor. ...
We chose the sinusoidal version because it may allow the model to extrapolate to sequence lengths longer than the ones encountered during training. ~Attention is all you need. 為什麼不用學得引數而採用sinusoid函式呢?sinusoidal函式並不受限於序列長度,其可以在遇到訓練集中未出現過的序列長度時仍能很...
为什么不用学得参数而采用sinusoid函数呢?sinusoidal函数并不受限于序列长度,其可以在遇到训练集中未出现过的序列长度时仍能很好的“extrapolate.” (外推),这体现了其具有一些inductive bias。对于2,shaw et al.2018中的相对位置编码Tensor是两个需要参数学习的tensor. ...