live_demo.ipynb - 12 hours (and counting) to optimise model on Jetson Nano - is this normal?

[jsynnott]

Hi everyone, I have recently setup trt_pose on a fresh Jetson Nano, all requirements installed including PyTorch v1.6 and torchvision v0.7.0 on Jetpack 4.4.

I am trying to run the live demo in jupyter notebook. The following line has taken 12 hours so far:

model_trt = torch2trt.torch2trt(model, [data], fp16_mode=True, max_workplace_size=1<25)

Is this normal? Surely it can't be?

[jsynnott]

Just an update. I killed the process as it didn't appear to be doing anything. I have managed to complete the model optimisation by:

• Installing https://pypi.org/project/jetson-stats/ and using it to enable 6GB of swap memory.
• Replacing the original line outlined in the original post, with the following (the line is the same, just wrap it with the 'with' statement:

with torch.cuda.device(0):
    model_trt = torch2trt.torch2trt(model, [data], fp16_mode=True, max_workplace_size=1<25)

[SijinJohn]

Hi even I have this problem. It is taking too long and the system is stuck. I also got a low memory warning on the Jetson nano.What to do???

[tucachmo2202]

Hi, I think you should export the torch model to onnx first then convert onnx to tensorrt engine.