For the edge cases it will use a quicker computation than std::asin()
My best theory: the fused standard path wins because XLA sees the entire softmax(Q @ K.T) @ V expression at once and compiles it into one optimized kernel — no intermediate matrices spilling to HBM. My flash attention uses fori_loop, which XLA likely compiles as a generic sequential loop. It probably can’t fuse across iterations, can’t pipeline memory loads, can’t interleave independent work. (I haven’t dumped the HLO to verify this — it’s an inference from the benchmark numbers and XLA’s documented behavior.)
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