[Inference Reproduce] The influence of GPU and Pytorch #10
KainingYing
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We release the weights of
R50_YTVIS19
, you can download it here. You can evaluate this checkpoint on your own machine and get an expected score55.1 AP
However, some users (#3 (comment)) said the inference can not match the performance (~55.1 AP) on paper or repos. We argue this is introduced by the mismatch of the required Pytorch version or GPU version.
In this issue, we evaluate this checkpoint on different combinations of Pytorch (1.x, 2.x) and Nvidia GPU (RTX 3060, 3090, 4090, A6000). We use Python 3.10 as the main environment.
We find that the GPU model and Pytorch environment can both affect the AP. Surprisingly, the RTX 3090 is about 1 point lower than the others.
It's normal for VIS to fluctuate during training, but it's very strange that it fluctuates so much during testing. We would be very grateful if someone could advise what is causing this.
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