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One final thing that made implementing FlexAttention quite fun is that we were able to leverage a lot of existing PyTorch infra in an interesting way
from the top result below
https://pytorch.org/blog/flexattention/
This operates as a sort of “software lottery” for ML researchers – if your attention variant doesn’t fit into one of the existing optimized kernels, you’re doomed to slow runtime and CUDA OOMs