OpenDriveLab / TCP

[NeurIPS 2022] Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline.
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High CPU usage during evaluation #29

Open HanaRo opened 1 year ago

HanaRo commented 1 year ago

First thank you for sharing the source code and datasets. Really an excellent work.

However, When I following the manual to run the evaluation by sh leaderboard/scripts/run_evaluation.sh, I found out the python process has an extremely high CPU usage (basically about 6000%). And I also check the usage of GPU (single 4090), only 2.3G of memory usage and average 5% volatile gpu-util, basically idle. Is that mean it was just using CPU to run the model?

So I wonder if it is a normal case and is there any suggestion about how to dealing with that? Thank you!

sqb2145 commented 1 year ago

Hi,

Can you please help me with running the run_evaluation.sh file. Like how you edited the file and where you placed the ckpt file.

Thank You!

penghao-wu commented 1 year ago

Hi, your 2.3G GPU memory usage is expected. In my case, the python script has a ~180% CPU usage and the CarlaUE4 has a ~200% CPU usage.

HanaRo commented 1 year ago

Hi, your 2.3G GPU memory usage is expected. In my case, the python script has a ~180% CPU usage and the CarlaUE4 has a ~200% CPU usage.

@WPH-commit Thanks for the information! But still I'm confused about why it utilizes so much CPU rather than GPU in my case. Since my evaluation in running on a shared server, it's kind of unaffordable for a single process using up the CPU. Please let me know if I need to provide more information. Thx!

HanaRo commented 1 year ago

Hi,

Can you please help me with running the run_evaluation.sh file. Like how you edited the file and where you placed the ckpt file.

Thank You!

@sqb2145 In my case, I edited the 'CARLA_ROOT' and 'TEAM_CONFIG' in the script. For the ckpt file, I put it at '${TCP_ROOT}/xxx/xx.ckpt', so the 'TEAM_CONFIG' is edited to 'xxx/xx.ckpt' Hope this will help you :)

penghao-wu commented 1 year ago

But still I'm confused about why it utilizes so much CPU rather than GPU in my case. Since my evaluation in running on a shared server, it's kind of unaffordable for a single process using up the CPU.

Could you check the GPU usage for the Carla server? It should be around 1G.

HanaRo commented 1 year ago

But still I'm confused about why it utilizes so much CPU rather than GPU in my case. Since my evaluation in running on a shared server, it's kind of unaffordable for a single process using up the CPU.

Could you check the GPU usage for the Carla server? It should be around 1G.

@WPH-commit Yes CARLA server basically run as you said, with about 1G memory, 200% CPU and about 30% GPU.

sqb2145 commented 1 year ago

Hi, Can you please help me with running the run_evaluation.sh file. Like how you edited the file and where you placed the ckpt file. Thank You!

@sqb2145 In my case, I edited the 'CARLA_ROOT' and 'TEAM_CONFIG' in the script. For the ckpt file, I put it at '${TCP_ROOT}/xxx/xx.ckpt', so the 'TEAM_CONFIG' is edited to 'xxx/xx.ckpt' Hope this will help you :)

Hi, Thank you for your reply. I think the issue I'm having isn't because of placing the ckpt file in the wrong directory. I'll try to figure it out. Thanks a lot! :)

Naive-Bayes commented 1 year ago

Hi, your 2.3G GPU memory usage is expected. In my case, the python script has a ~180% CPU usage and the CarlaUE4 has a ~200% CPU usage.

@WPH-commit Thanks for the information! But still I'm confused about why it utilizes so much CPU rather than GPU in my case. Since my evaluation in running on a shared server, it's kind of unaffordable for a single process using up the CPU. Please let me know if I need to provide more information. Thx!

I think this problem is not because the model, but the Carla Simulator. When do the open-loop training, it really faster than eval. But when we do close-loop evaluation, it is so slow. Actually, I also do not have the solution to accelerate the simulation process,sad.