About speed

[Emiria96]

Hi authors, I have some questions about the speed of your method. I downloaded your pretrained resnet-101 model weight and ran it with a Titan RTX (24GB) GPU, the inference speed is about 1 second/per img.
d2.evaluation.evaluator INFO: Inference done 1144/1250. Dataloading: 0.0014 s/iter. Inference: 0.9478 s/iter. Eval: 0.0187 s/iter. Total: 0.9679 s/iter. ETA=0:01:42
In your paper you report with resnet-101 dcn, your model can run at 6.1FPS also using a Titan RTX GPU. So how could I get the same inference speed as given in your paper?
By the way, the inference speed of PointRend is about 0.1 second/per img, which is 10x faster of your model in my experiment.
d2.evaluation.evaluator INFO: Inference done 987/1250. Dataloading: 0.0014 s/iter. Inference: 0.0888 s/iter. Eval: 0.0190 s/iter. Total: 0.1093 s/iter. ETA=0:00:28
Waiting for your reply.

[lkeab]

This is not the final code implementation. I would have a final updating on this soon.