Hello,
v1 : BatchSize x MaxSentenceLength x EmbSize
v2 : BatchSize x EmbSize x MaxSentenceLength
and
v3 = torch.bmm(v1, v2) : BatchSize x MaxSentenceLength x MaxSentenceLength
As I understand - torch.bmm based on simple dot product of 2 two embeddings:
                               sum(emb1[i] * emb2[i],  i = [0..EmbSize])

But for me interesting version of torch.bmm based on weighted dot product of 2 embeddings:
                               sum(w[i] * emb1[i] * emb2[i],  i = [0..EmbSize])

where  w[i] are learned weights.
Is there a way to do this ?
Thanks in advance!