Comments (20)
Sent a PR: osrf/rocker#182
If it's not accepted, I'll add the following block in the Dockerfile.
## Set env for nvidia-container-runtime
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
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Yes indeed, my latest
is older than galactic-latest
:
ghcr.io/autowarefoundation/autoware-universe galactic-latest ea6b0e03f964 5 weeks ago 5.74GB
ghcr.io/autowarefoundation/autoware-universe latest 35694ec40e8f 8 weeks ago 16.2GB
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@angry-crab humble-latest
doesn't contain CUDA now. Please use humble-latest-cuda
instead.
https://github.com/autowarefoundation/autoware/pkgs/container/autoware-universe/26944787?tag=humble-latest-cuda
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@kenji-miyake
I'm sorry for the late replay. AND thank you for identifying the cause of this issue!
I will close this issue after creating a PR to add your suggestion into the document.
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I get the same problem
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I think this will be resolved after we change the base image to 11.7.0-devel-ubuntu22.04.
But to do that, the network installation packages of cuDNN and TensorRT should be released.
https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/
I'm waiting for that.
Or if there is another better approach, I can try it out.
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I think this will be resolved after we change the base image to 11.7.0-devel-ubuntu22.04.
But to do that, the network installation packages of cuDNN and TensorRT should be released. https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/
I'm waiting for that. Or if there is another better approach, I can try it out.
Do you have any other method to solve this problem?
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Regarding nvidia-smi
, I guess it's fixed by installing nvidia-utils
.
$ apt-file search $(which nvidia-smi)
nvidia-340: /usr/bin/nvidia-smi
nvidia-utils-390: /usr/bin/nvidia-smi
nvidia-utils-418-server: /usr/bin/nvidia-smi
nvidia-utils-435: /usr/bin/nvidia-smi
nvidia-utils-440: /usr/bin/nvidia-smi
nvidia-utils-450-server: /usr/bin/nvidia-smi
nvidia-utils-460-server: /usr/bin/nvidia-smi
nvidia-utils-470: /usr/bin/nvidia-smi
nvidia-utils-470-server: /usr/bin/nvidia-smi
nvidia-utils-510: /usr/bin/nvidia-smi
nvidia-utils-510-server: /usr/bin/nvidia-smi
Regarding cudaErrorInsufficientDriver
, I'm sorry but I'm not sure. 🥺
I need to investigate the issue to catch up.
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Regarding
nvidia-smi
, I guess it's fixed by installingnvidia-utils
.$ apt-file search $(which nvidia-smi) nvidia-340: /usr/bin/nvidia-smi nvidia-utils-390: /usr/bin/nvidia-smi nvidia-utils-418-server: /usr/bin/nvidia-smi nvidia-utils-435: /usr/bin/nvidia-smi nvidia-utils-440: /usr/bin/nvidia-smi nvidia-utils-450-server: /usr/bin/nvidia-smi nvidia-utils-460-server: /usr/bin/nvidia-smi nvidia-utils-470: /usr/bin/nvidia-smi nvidia-utils-470-server: /usr/bin/nvidia-smi nvidia-utils-510: /usr/bin/nvidia-smi nvidia-utils-510-server: /usr/bin/nvidia-smi
Regarding
cudaErrorInsufficientDriver
, I'm sorry but I'm not sure. 🥺 I need to investigate the issue to catch up.
I also encontered the similar problem. When I run "colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release" in the container of "ghcr.io/autowarefoundation/autoware-universe:latest" image , I found "CUDA_TOOLKIT_ROOT_DIR not found or specified
CUDA NOT FOUND
TensorRT is NOT Available
CUDNN is NOT Available" error. It seems the container could not find CUDA. How do I fix this problem? Do I need to install autoware from the source instead of the docker?
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@may012345 Seeing @yukke42 -san's comment, I guess you can run Autoware using pure Docker
, not rocker
.
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Yes. I could run autoware with adocker run
command and a image built locally following the official tutorial.
docker run --rm -it --gpus all -e DISPLAY -e TERM -e QT_X11_NO_MITSHM=1 -v /tmp/.X11-unix:/tmp/.X11-unix -v /etc/localtime:/etc/localtime:ro ghcr.io/autowarefoundation/autoware-universe:humble-latest
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@may012345 Seeing @yukke42 -san's comment, I guess you can run Autoware using pure
Docker
, notrocker
.
I run with "rocker --nvidia --x11 --user --volume $HOME/autoware -- ghcr.io/autowarefoundation/autoware-universe:latest" and met the problem.
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I've also met the same problem. I'm using rocker --nvidia --x11 --user --volume $HOME/autoware -- ghcr.io/autowarefoundation/autoware-universe:latest
.
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I have the problem with rocker --nvidia --x11 --user --volume $HOME/autoware -- ghcr.io/autowarefoundation/autoware-universe:galactic-latest
but not with rocker --nvidia --x11 --user --volume $HOME/autoware -- ghcr.io/autowarefoundation/autoware-universe:latest
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but not with rocker --nvidia --x11 --user --volume $HOME/autoware -- ghcr.io/autowarefoundation/autoware-universe:latest
@VRichardJP Could you tell me the hash of your images like this? I guess one is old (and based on CUDA image).
$ docker images | grep autoware-universe | grep " latest "
ghcr.io/autowarefoundation/autoware-universe latest 5fdadcabfe9c 5 weeks ago 5.73GB
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docker run --rm -it --gpus all -e DISPLAY -e TERM -e QT_X11_NO_MITSHM=1 -v /tmp/.X11-unix:/tmp/.X11-unix -v /etc/localtime:/etc/localtime:ro -v $HOME/adehome:/home/adehome [ghcr.io/autowarefoundation/autoware-universe:humble-latest](http://ghcr.io/autowarefoundation/autoware-universe:humble-latest)
Using docker
instead of rocker
does not solve the problem. CUDA, TensorRT, and cuDNN could not be found.
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I found the problem is because of the env NVIDIA_DRIVER_CAPABILITIES
.
To confirm that, run the following command.
rocker --nvidia --x11 --user --env NVIDIA_DRIVER_CAPABILITIES="" -- ghcr.io/autowarefoundation/autoware-universe:humble-latest-cuda
# Or
rocker --nvidia --x11 --user --env NVIDIA_DRIVER_CAPABILITIES=compute,utility,graphics -- ghcr.io/autowarefoundation/autoware-universe:humble-latest-cuda
I'll investigate this behavior more in detail and fix it.
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@yukke42 My PR to rocker
is merged. Do you think we can close this issue?
We can set NVIDIA_DRIVER_CAPABILITIES
manually until the new rocker
is released.
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@.kenji-miyake I'm sorry for the late replay. AND thank you for identifying the cause of this issue! I will close this issue after creating a PR to add your suggestion into the document.
I will do after this related issue is closed.
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Resolved by #2732
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Related Issues (20)
- Implementing BEVDet in Autoware HOT 4
- Create Dense Urban ODD Scenarios HOT 3
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- Report results of the weekly scenario tests publicly as dashboard
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- Docker Image OpenADK with CUDA support has an issue with CUDA installation HOT 2
- Prune and document the docker packages HOT 3
- Migration from autoware_auto_msgs to autoware_msgs
- Enhancing scenario_simulator_v2 to print or visualize parameters/modifiers used for test iterations
- When the display scale is set to 200% the Rviz window always crashes HOT 1
- `docker-build-and-push` should not push an image for every commit to main
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- compare_map_segmentation
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