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I am currently testing my models in Triton Server and I observed interesting behaviour.
More specifically I observed this behaviour on RTMDet family of models.
I tested two variants for deployment:
RTMDET in TRT - TensorRT backend + custom ops in .so files
RTMDET in TRT - Python backend + mmdeploy_runtime_gpu + model.py inference script
I noticed that when using pure TRT the speed is 5 times, sometimes even more, lower than when using python backend and mmdeploy_runtime_gpu
I am still wondering why this is, as in my mind the speed should be higher as there should be less calls when executing only TRT model without the runtime.
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Hello,
I am currently testing my models in Triton Server and I observed interesting behaviour.
More specifically I observed this behaviour on RTMDet family of models.
I tested two variants for deployment:
I noticed that when using pure TRT the speed is 5 times, sometimes even more, lower than when using python backend and mmdeploy_runtime_gpu
I am still wondering why this is, as in my mind the speed should be higher as there should be less calls when executing only TRT model without the runtime.
Any ideas?
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