Hi, I insatlled trt_pose and run sample code
Howerver it took too long running time.
I checked GPU resource by JTOP while running the code,
and I found that jetson nano doesn't use GPU while running.
I'm using
pytorch 1.8
torchvision 0.9.0
jetpack 4.6
CUDA 10.2.300
opencv 4.5.4 compiled CUDA : YES
TensorRT 8.0.1.6
and swap memory 8GB
t0 = time.time()
torch.cuda.current_stream().synchronize()
for i in range(50):
y = model_trt(data)
torch.cuda.current_stream().synchronize()
t1 = time.time()
print(50.0 / (t1 - t0))
it reported value : 5~ 6
I think it should be more than 10,
but it's low
I think that's because it's not using GPU resource.
Hi, I insatlled trt_pose and run sample code Howerver it took too long running time. I checked GPU resource by JTOP while running the code, and I found that jetson nano doesn't use GPU while running.
I'm using pytorch 1.8 torchvision 0.9.0 jetpack 4.6 CUDA 10.2.300 opencv 4.5.4 compiled CUDA : YES TensorRT 8.0.1.6 and swap memory 8GB
when I checked running time by using below code,
model_trt = TRTModule() model_trt.load_state_dict(torch.load(OPTIMIZED_MODEL))
t0 = time.time() torch.cuda.current_stream().synchronize() for i in range(50): y = model_trt(data) torch.cuda.current_stream().synchronize() t1 = time.time()
print(50.0 / (t1 - t0))
it reported value : 5~ 6
I think it should be more than 10, but it's low
I think that's because it's not using GPU resource.
How can I solve this problem?