God bless people who implement models from academic articles that should frankly include them to begin with. What's more is that this implementation has clear instructions for extending this to your datasets.
> academic articles that should frankly include them to begin with.
Boo hoo. Researchers tell the world for free exactly how to implement their state-of-the-art work (which probably cost north of $1M to develop) and promise to release code, and we're indignant because they didn't do it quite fast enough for us.
(1) It's not free when the research is funded by public tax dollars (which I grant is not always, but often the case).
(2) I'm not aware of this promise you're speaking of... my understanding is that authors of papers are under no obligation to produce any implementation, let alone usable, documented implementations.
> (1) It's not free when the research is funded by public tax dollars (which I grant is not always, but often the case).
The work was done at FAIR (Facebook), so that's not applicable here.
> (2) I'm not aware of this promise you're speaking of... my understanding is that authors of papers are under no obligation to produce any implementation, let alone usable, documented implementations.
Look at the paper [1], it's the last sentence of the abstract: "Code will be made available."
Very rarely do these papers contain all the tricks needed to replicate the exact results presented. Usually, if you follow the paper to the letter you won’t get the same thing in the end. In particular training regimes and the particulars of data augmentation are often omitted “for brevity“.
It was just in Lua.