Docker settings on a step

You have the option to customize the Docker settings at a step level.

By default every step of a pipeline uses the same Docker image that is defined at the pipeline level. Sometimes your steps will have special requirements that make it necessary to define a different Docker image for one or many steps. This can easily be accomplished by adding the DockerSettings to the step decorator directly.

from zenml import step

from zenml.config import DockerSettings

@step(

settings={

"docker": DockerSettings(

parent_image="pytorch/pytorch:1.12.1-cuda11.3-cudnn8-runtime"

def training(...):

...

Alternatively, this can also be done within the configuration file.

steps:

training:

settings:

docker:

parent_image: pytorch/pytorch:2.2.0-cuda11.8-cudnn8-runtime

required_integrations:

gcp

github

requirements:

zenml  # Make sure to include ZenML for other parent images

numpy

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Last updated 15 days ago