Going through the Transformer paper, and its implementation, I have had a question:

In the self-attention routine in the encoder, is it plausible to compute q dot q instead of q dot k when calculating scores for each input token?

I see that in the self-attention, the memory_antecedent = query_antecedent and q, k, v is computed (and trained) separately (c.f. compute_qkv in T2T).

Would utilizing the same q for the computation of scores (rather than having a separate k) seriously deteriorate the performance?