Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
Significant Increase in Initialization Time for YOLOX TensorRT Model on NVIDIA-Jetson Nano 4gb
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- Dominant language
- Python
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Description
After converting the YOLOX model to TensorRT, the initialization time on an NVIDIA Jetson Nano 4GB has unexpectedly increased from 1:30 minutes to approximately 5 minutes over a period of time. The pytorch model was converted into tensorRT using the trt module provided by yolox tools that outputs a model_trt.pth file. Is this issue related to caching of yolox?
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Research direction
Start with the YOLOX trt module that converts the PyTorch model into model_trt.pth, then reproduce initialization on the NVIDIA Jetson Nano 4GB and compare the reported times. Investigate whether caching explains the increase from about 1:30 to 5 minutes; done means identifying the cause and reporting a reproducible explanation or fix.
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Assessment
- Tech stack
- python, pytorch
- Domain
- embedded-iot, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 22/100