Soft-RFDETR : An optionnal Mixture of Experts Module to RFDETR #245
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Description
Hello, I propose here an optional soft mixture of experts implementation for RF-DETR. The idea comes from the article From Sparse to Soft Mixtures of Experts, and it seems to usually improve the overall performance of a model. I thought that it would be a nice option to add.
As the article suggests, I set the default value of experts per slots to 1.
In order to add this option we would need to add the python library "soft_moe". This library offers good a Soft MoE Wrapper, the source code is available here.
Type of change
Please delete options that are not relevant.
How has this change been tested, please provide a testcase or example of how you tested the change?
I tested it on a small private dataset and it improved a bit the accuracy (I gained roughly 1% mAP, so a small gain but still a gain). I am not able to test it on the full COCO dataset but I guess it would also improve a bit the overall accuracy.
As expected the MoE RF-DETR model is slightly slower than the basic one, but still very fast.