Notebook 1 <eos> problem.

[yusufsali61]

Hi, first of all thanks for sharing your great work. It is really helpful.

In the seq2seq model definition part, you say The last token input into the decoder is the one before the [EOS] token - the [EOS] token is never input into the decoder.
However, in code decoder loops until the length of target sequence is reached. So it doesn't check if the current output is [EOS] or not. So even if we see [EOS] at some time step, we continue until length of target is reached. So for example if ground truth is ["a", "b", "c", "d", "[EOS]"], it is possible that our prediction will be ["x", "y", "[EOS]", "z", "t"] or ["x", "y", "[EOS]", "z", "[EOS]"] or ["x", "y", "k", "z", "t"]. And due to same reason, it can't be used for inference because forward method depends on target length. Am I missing something?

[zjysteven]

Same question here. Did you figure out anything by any chance @yusufsali61 ?

[NickleDave]

Hi @yusufsali61 and @zjysteven I had the same question.
You might find this implementation from @sooftware helpful:
https://github.com/sooftware/seq2seq/blob/646c3cd70f19c761a657cb7ea7a54be04934a58d/seq2seq/model/decoder.py#L95