localminimum / localminimum/R-net
Question about question-passage attention
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 319
- Forks
- 121
- PR merge metrics
- No merged PRs in 30d
Description
when the network process the attention match rnn, in the first loop, it actually process question - passage attention. In the function 'attention_rnn' when it calls attention, the outputs_ is [ [ batch, max_p_len, attn_size * 2], [batch, max_q_len, attn_size + 2] ] , i wonder how the outputs = sum(outpus_) run ? Their dimensions are not matched.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start in the attention_rnn function and follow its call to attention, focusing on how outputs_ is constructed and combined. Trace the tensor shapes for the question and passage paths and check the operation that produces outputs. Done means the dimension handling is understood and the issue's question is answered or a concrete mismatch is identified.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100