Function of type `job`#

You can deploy a model using a ~mlrun.runtimes.KubejobRuntime type function, which runs the code in a Kubernetes Pod.

You can create (register) a job function with basic attributes such as code, requirements, image, etc. using the set_function() method. You can also import an existing job function/template from the Function hub .

Functions can be created from a single code, notebook file, or have access to the entire project context directory. (By adding the with_repo=True flag, the project context is cloned into the function runtime environment.)

Examples:

# register a (single) python file as a function
project.set_function(
    "src/data_prep.py",
    name="data-prep",
    image="mlrun/mlrun",
    handler="prep",
    kind="job",
)

# register a notebook file as a function, specify custom image and extra requirements
project.set_function(
    "src/mynb.ipynb",
    name="test-function",
    image="my-org/my-image",
    handler="run_test",
    requirements=["scikit-learn"],
    kind="job",
)

# register a module.handler as a function (requires defining the default sources/work dir, if it's not root)
project.spec.workdir = "src"
project.set_function(
    name="train",
    handler="training.train",
    image="mlrun/mlrun",
    kind="job",
    with_repo=True,
)

To run the job:

project.run_function("train")

See also

Function of type job

Function of type job#

Function of type `job`#