The concept is simple. For a model with $N$ layers, I define a configuration $(i, j)$. The model processes layers $0$ to $j{-}1$ as normal, then loops back and reuses layers $i$ through $j{-}1$ again, and then the rest to $N{-}1$. The layers between $i$ and $j{-}1$ get duplicated in the execution path. No weights are changed. The model just traverses some of its own layers twice.
Европейская страна обвинила США и Израиль в нарушении международного права20:06
。业内人士推荐新收录的资料作为进阶阅读
There is reason to be optimistic though.
Педиатр раскрыла требующую обращения к врачу температуру у ребенка07:50
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