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This is not an official implementation, so there is a slight difference in the number of parameters.
Of course, I tried to implement it as similar as possible to the contents of the paper. :).
This is kind of weird. I test several open-source Conformer implementation (I also implement it myself), but none of them can strictly match the reported number of parameters. Do you have any idea where the difference may be?
btw. num_classes is set to 1k according to the paper.
In the Conformer original paper, the number of parameters are
![截屏2021-10-18 下午3 22 54](https://user-images.githubusercontent.com/32546978/137686405-db7c6c99-a33d-414c-abb0-a72887d1e8c6.png)
However, with the implementation in this repo, the number of parameters are slightly different
I get the size with this script
Since the convolution layer kernel size couldn't be set to 32, I just set it to 31. But this won't make such difference in number of params.
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