google-deepmind / google-deepmind/tapnet
GPU PyTorch slower than cpu
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Description
Hi, I am running the standard PyTorch TAPIR model on GPU but noticed that the inference speed is significantly slower than when using cpu. This seems backwards. I am running on 400 frames with only 2 query points. The frame size is 512x512x3. I see that it is in fact running on the GPU due to the usage percentage increasing and the memory increases as well. I am also running on a NVIDIA GeForce RTX 2080. Any guidance on what could be happening here?
CPU: ~325s to complete inference
GPU: ~1025s to complete inference
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