localminimum / localminimum/QANet
The embedding projection
- Dominant language
- Python
- Stars
- 985
- Forks
- 297
- PR merge metrics
- No merged PRs in 30d
Description
Hi, I have noticed that you have put the input projection before Highway Network. However, in the paper, it is mentioned that the input of Embedding Encoding Layer is a vector of dimension p1+p2=500 for each word, which means that the projection is placed after the Highway Network.
Have you already try this?
Contributor guide
No contributing guide indexed for this repository
Research direction
The issue names no files or tests. Compare the implementation's embedding projection and Highway Network order with the paper's stated p1+p2=500 input, then determine which ordering is intended; done means a documented decision supported by an implementation check or experiment.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100