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Hi all, first, thanks for this great work.
I encounter a weird issue while testing decord on GPU on my computer. I am running the following benchmark command:
python3 bench_decord.py --file /my_video.mp4 for CPU python3 bench_decord.py --file /my_video.mp4 --gpu 0 for GPU
python3 bench_decord.py --file /my_video.mp4
python3 bench_decord.py --file /my_video.mp4 --gpu 0
It is working fine on CPU ending with the following line:
300 frames, elapsed time for random access(accurate): 25.084531545639038
But on GPU it deadlocks almost right away after this line:
[h264 @ 0x171d080] mmco: unref short failure
This appends while running localy or through docker (from decord/gpu.Dockerfile) with nvdia-runtime enabled
Here is my nvidia-smi output (its the same locally or from inside the docker):
NVIDIA-SMI 470.63.01 Driver Version: 470.63.01 CUDA Version: 11.4
From inside the docker I don't see any process lines in nvdia-smi, but locally I crealy see the process line jumping onto the GPU as here:
| 0 N/A N/A 5444 C python3 205MiB |
GPU usage keep very low, and it deadlocks for ever.
Do I have to switch to another version of CUDA maybe ?
Thanks a lot.
The text was updated successfully, but these errors were encountered:
I meet the same problem, have you solved it?
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Hi all,
first, thanks for this great work.
I encounter a weird issue while testing decord on GPU on my computer.
I am running the following benchmark command:
It is working fine on CPU ending with the following line:
But on GPU it deadlocks almost right away after this line:
This appends while running localy or through docker (from decord/gpu.Dockerfile) with nvdia-runtime enabled
Here is my nvidia-smi output (its the same locally or from inside the docker):
From inside the docker I don't see any process lines in nvdia-smi, but locally I crealy see the process line jumping onto the GPU as here:
GPU usage keep very low, and it deadlocks for ever.
Do I have to switch to another version of CUDA maybe ?
Thanks a lot.
The text was updated successfully, but these errors were encountered: