Encoder-Decoder Model

Dear all,

I had a look at the encoder-decoder architecture following the seminal paper "Attention is all you need".

After doing experiments on my own and doing further reading, I found many sources saying that the (maximum) input lengths of encoder and decoder are usually the same, or that there is no reason in practice to use different legnths (see e.g. [https://stats.stackexchange.com/questions/603535/in-transformers-for-the-maximum-length-of-encoders-input-sequences-and-decoder](https://stats.stackexchange.com/questions/603535/in-transformers-for-the-maximum-length-of-encoders-input-sequences-and-decoder)).

What puzzles me is the "usually". I want to understand the thing on the mathematical level, and I …

architecture attention attention is all you need decoder deeplearning encoder encoder-decoder look paper practice reason