Fairseq: RoBERTa and 514

[LysandreJik]

Hi! We're scratching our heads with RoBERTa and the way it handles its inputs.

The following matrix is of size 514x768:

from fairseq.models.roberta import RobertaModel

model = RobertaModel.from_pretrained("../roberta.base")
print(model.model.decoder.sentence_encoder.embed_positions.weight.size())

# torch.Size([514, 768])

Why is it different from the maximum embedding size which is 512? Furthermore, we observe that the second column of this matrix is full of zeros:

print(model.model.decoder.sentence_encoder.embed_positions.weight[1, :])
# tensor([0., 0., 0., 0., 0., 0., 0., 0. ... 

Why is that? Thank you.

[lematt1991]

Yes padding_idx is usually equal to 1, so it should always be a vector of all zeros. The positional embeddings then start at padding_idx+1 (i.e. 2 - 514). Hope this clears it up!

[LysandreJik]

Ah okay, that makes sense. In this case, what is the first column, is it full of randomly initialized values? In that case, why not use padding_idx = 0? Thank you for your answer.

[lematt1991]

Yeah the first vector is randomly initialized values that never get used. There's really no particular reason why padding_idx is 1 instead of 0, other than it's the first token added to the dictionary. We need to use the same padding_idx value for both embed_tokens and embed_positions

[LysandreJik]

Okay, I understand. Thank you very much for your help!