@Marvin How to pass docker run argument "--gpus 0" when running flow in container using Docker work pool?

To pass the

--gpus 0

argument when running a flow in a container using Prefect's Docker work pool, you need to configure the Docker work pool settings. Unfortunately, the specific documentation on passing GPU arguments directly wasn't found in the Prefect 3.x documentation. However, you can generally pass additional Docker arguments by configuring the Docker work pool appropriately. Here's a general approach you can take: 1. Configure Docker Work Pool: Ensure that your Docker work pool is set up correctly. You can do this through the Prefect UI or via the CLI. 2. Modify Docker Command: When setting up your Docker work pool, you can specify additional configuration that might allow you to include GPU settings. This might involve customizing the Docker command used to start the containers. 3. Using Environment Variables or Dockerfile: Sometimes, you may need to modify the Dockerfile or use environment variables to configure GPU usage if direct command-line arguments are not supported. 4. Consult Prefect Community or Support: If the documentation doesn't provide a direct solution, consider reaching out to the Prefect community or support channels for specific advice on GPU configuration. For more detailed guidance, you might want to refer to the Prefect Docker infrastructure examples or explore community forums and GitHub issues related to Prefect. If you have further questions or need more specific assistance, feel free to ask!

@Marvin Is there a way to pass docker run arguments in job_variables?

Yes, you can pass Docker run arguments using

job_variables

in Prefect's Docker work pool. Here's how you can do it: 1. Define Job Variables: You can specify Docker run arguments in the

job_variables

section of your

prefect.yaml

file or pass them as a dictionary to the

job_variables

argument of the

.deploy()

method in your Python script. 2. Override Defaults: These job variables can override any values set on the work pool or deployment. This means you can customize the Docker run command for specific deployments or flow runs. 3. Use in CLI or UI: You can pass these job variables when creating deployments or running flows, either through the Prefect UI or using the Prefect CLI. For example, in your

prefect.yaml

, you might have:

yaml
deployments:
  work_pool:
    job_variables:
      docker_run_args: "--gpus 0"

You can also pass these variables programmatically:

python
from prefect.deployments import Deployment

deployment = Deployment.build_from_flow(
    flow=my_flow,
    name="my_deployment",
    work_pool_name="my-docker-pool",
    job_variables={"docker_run_args": "--gpus 0"}
)
deployment.apply()

For more details, you can refer to the Prefect documentation on customizing work pools.

@Marvin when creating docker work pool what are Command and Labels fields? What are defaults? Can I set here docker run arguments like "--gpus 0"? How?

Unfortunately, the specific details about the "Command" and "Labels" fields in the Prefect Docker work pool configuration, including their defaults and how they can be used to pass Docker run arguments like

--gpus 0

, are not explicitly available in the documentation excerpts I retrieved. However, generally speaking: - Command Field: This typically specifies the command that will be run inside the Docker container. It might be possible to append arguments here if the work pool configuration supports it. - Labels Field: Labels are often used for metadata or to categorize and filter resources. They are unlikely to be used for passing runtime arguments to Docker. If you want to pass Docker run arguments like

--gpus 0

, you might need to explore using job variables or environment variables as mentioned earlier, or consult the Prefect community for more advanced customization options. For precise instructions, it would be beneficial to refer to the Prefect documentation on Docker infrastructure or reach out to the Prefect community for specific guidance on configuring these fields.