Winograd convolutions cost us 2 mAP and we didn't notice for a month
TL;DR: We turned on Winograd convolution to shave latency off a pedestrian detector running on a Cortex-A53, got a clean 18% speedup, and silently lost 2.1 mAP because the F(4,3) transform overflowed in fp16. The accuracy drop hid inside our aggregate metric for almost a month before a per-distance
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