Comments (2)
Hi @chenghuige , thanks for your issue. There are a few points we need to clarify:
First of all, we don't claim our model to be faster than R-Net implementation by HKUST. Secondly, in the paper they use P100, which is one of the latest gpus with twice the gpu memory of GTX1080 which I used to develop this model. Last but not least, the speed claimed by QANet paper is when the batch size of 32 is used, not 64.
Having said that, I agree with you that my implementation is probably not as fast as the original paper's implementation. If you have a suggestion or ideas to make this implementation better, please push a pull request. Thanks!
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@localminimum I see, actually I learn a lot from your code, thanks a lot for sharing!
I'm trying to find encoder for applications like classification which is faster then rnn and has similar or better performance. Since google claims their model is much faster then rnn based models, so very curious if we can verify that :) Anyway I will first close this issue.
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Related Issues (20)
- https://nlp.stanford.edu/data/glove.840B.300d.zip HOT 2
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