localminimum / localminimum/QANet

The embedding projection

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Dominant language
Python
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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?

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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

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