Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

The figure below depicts the self-attention part of a decoder.
Figure 9.28 - Decoder with self-attention (simplified)
Once again, we can dive deeper into the inner workings of the self-attention
mechanism.
Figure 9.29 - Decoder with self-attention
There is one small difference in the self-attention architecture between encoder
and decoder: The feed-forward network in the decoder sits atop the cross-attention
mechanism (not depicted in the figure above) instead of the self-attention
mechanism. The feed-forward network also maps the decoder’s output from the
dimensionality of the model (d_model) back to the number of features, thus
yielding predictions.
Self-Attention | 749