Hi! I'm working through the simple ML flyte demo. ...
# ask-the-community
Hi! I'm working through the simple ML flyte demo. I am trying to figure out how far you can go with the
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❯ pyflyte run --remote example.py training_workflow --hyperparameters '{"C": 0.1}'
Go to <http://localhost:30080/console/projects/flytesnacks/domains/development/executions/fa1c65afdde414c7d961> to see execution in the console.
syntax when you have custom dependencies as specified in
. I got excited that the run command was somehow passing
along, but now I see that
is simply preinstalled in the base image. I am curious if there a way to handle custom dependencies without dropping out of the simple
pyflyte run
command and without having to have a "kitchen sink" style base image?
Looks like my question is probably directly addressed by the docs... working through this now https://docs.flyte.org/projects/cookbook/en/latest/getting_started/creating_flyte_project.html#creating-a-flyte-project
you can also build a new image with custom dependencies, and use
pyflyte run --image <new_image_name> …
cool! I saw you can also include a
@task(..., container_image=myimage)
but I think that gets ignored when you use
pyflyte run
is that accurate? Those get honored when you use
pyflyte register
by default, all the tasks will use the image you pass in pyflyte run. if you want to use different image for specific task, you could pass the image in task decorator