Initial Query

nicholas@server:~/project$ sudo docker start myproject [sudo] password for nicholas: Error response from daemon: could not select device driver "" with capabilities: [[gpu]] Error: failed to start containers: myproject

LLM Generation

Query

nicholas@server:~/project$ sudo docker start myproject [sudo] password for nicholas: Error response from daemon: could not select device driver "" with capabilities: [[gpu]] Error: failed to start containers: myproject

Output

This error indicates that the container is configured to require GPU support but Docker couldn’t find an appropriate GPU driver (or runtime) to satisfy that capability. In other words, Docker sees that your container expects GPU access but isn’t being provided one. Here are some steps you can follow to troubleshoot and resolve the issue: 1. Verify Your GPU Setup:  • Make sure your system actually has a GPU installed.  • Confirm that the proper NVIDIA drivers (or the appropriate drivers for your GPU) are installed on the host.  • Run a command like nvidia-smi (if you have an NVIDIA GPU) to check if the GPU is recognized by the system. 2. Install and Configure the NVIDIA Container Toolkit:  • To run GPU-enabled containers, install the NVIDIA Container Toolkit by following NVIDIA’s installation guide.  • After installing, ensure that Docker is configured to use the NVIDIA runtime. In many cases, this involves editing your /etc/docker/daemon.json to include something like:   {    "default-runtime": "nvidia",    "runtimes": {     "nvidia": {      "path": "nvidia-container-runtime",      "runtimeArgs": []     }    }   }  • Restart the Docker daemon after making these changes. 3. Check Container Configuration:  • If your container was created with a GPU flag (for example, using --gpus all or a similar option), it expects access to GPU resources at every start.  • If you don’t actually need GPU access in this container, you can recreate it without specifying GPU requirements. 4. Starting the Container:  • Note that when you use docker start on an existing container it uses the configuration defined at creation time. If that configuration requests GPU capabilities and your host isn’t set up properly, you will get this error. Sometimes it’s simpler to remove the container and re-run it with:   sudo docker run --gpus all …  • Alternatively, if you don’t need GPU support, recreate the container omitting the GPU flag. By ensuring that your host has a working GPU driver setup and that Docker is configured to use the NVIDIA runtime (or the appropriate GPU support), you should be able to resolve this error.

Check if any of the following conditions are true:

Substring Evaluation

Testing if the previous output contains the string nvidia-docker2: False

Substring Evaluation

Testing if the previous output contains the string nvidia-container-toolkit: False

Final Answer: False

Initial Query

nicholas@server:~/project$ sudo docker start myproject [sudo] password for nicholas: Error response from daemon: could not select device driver "" with capabilities: [[gpu]] Error: failed to start containers: myproject

LLM Generation

Query

nicholas@server:~/project$ sudo docker start myproject [sudo] password for nicholas: Error response from daemon: could not select device driver "" with capabilities: [[gpu]] Error: failed to start containers: myproject

Output

That error indicates that Docker tried to start a container requesting GPU support, but it couldn’t find a GPU-enabled runtime (like NVIDIA’s container runtime) properly configured on your system. In other words, Docker was asked to provide the "gpu" capability, but no runtime capable of handling that request was available. Below are some steps to diagnose and fix the issue: 1. Verify Your Setup:  • Confirm that you have a supported NVIDIA GPU installed.  • Make sure the NVIDIA driver is correctly installed on your host system.  • Check that you have installed the NVIDIA container toolkit (formerly nvidia-docker2), which provides the NVIDIA container runtime. 2. Install or Reinstall the NVIDIA Container Toolkit:  • On Ubuntu, you can usually install it with:   sudo apt-get update   sudo apt-get install -y nvidia-docker2  • After installing, restart the Docker daemon:   sudo systemctl restart docker 3. Configure Docker to Use the NVIDIA Runtime:  • Edit or create the Docker daemon configuration file (/etc/docker/daemon.json) so that it includes something similar to:   {    "default-runtime": "nvidia",    "runtimes": {     "nvidia": {      "path": "nvidia-container-runtime",      "runtimeArgs": []     }    }   }  • Save the file and restart Docker again:   sudo systemctl restart docker 4. Check Your Container’s Run Command or Configuration:  • If you’re explicitly specifying GPU requirements (for example, using the --gpus flag or similar in a Docker Compose file or container configuration), ensure that it’s intended. If your container doesn’t require GPU support, remove those options.  • If it does need GPU access, verify that your Docker command is referencing the correct runtime. For example:   sudo docker run --gpus all [other-options] your_image 5. Verify the NVIDIA Docker Runtime:  • You can run a quick test by running an NVIDIA container:   sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi  • This should display your GPU information if everything is set up properly. By following these steps, you should be able to resolve the error by ensuring that Docker has the proper GPU driver/runtime available to start your container.

Check if any of the following conditions are true:

Substring Evaluation

Testing if the previous output contains the string nvidia-docker2: True

Substring Evaluation

Testing if the previous output contains the string nvidia-container-toolkit: False

Final Answer: True