Speeding up DETR Hungarian matching by 3.8–8.0× with grouped costs + batched CUDA

DETR variants have become much faster and more practical, but one part of the training path is still commonly implemented much like the original: Hungarian matching. (Illustration by GPT) https://preview.redd.it/w4x3baro8ajh1.png?width=1672&format=png&auto=webp&s=f5416161832f4b7d2636843e5c10bedd66668083 A typical matcher: constructs matching costs on the GPU, transfers them to the CPU, calls SciPy’s linear_sum_assignment , transfers assignments back to the GPU, and repeats this across images, auxiliary decoder outputs, and in Group-DETR-style training query groups. The individual assignment pr