got it ya that makes sense. I was using .init which worked great but
needed to be able to pass docker_args into the container running the task. Only way I saw that possible was with .create would like to execute it remotely would like the auto logs

hm SmugDolphin23 so I added this into the Task but I still do not get auto logging for a pytorch training task

but now I am just getting into weird situations were it seems like .create has the docker stuff I need but not logs and .init has the logs but not docker

been using this https://clearml.slack.com/archives/CTK20V944/p1671207870939899?thread_ts=1671206153.300929&cid=CTK20V944

so curious if this is just a me misuderstanding and not using the .init/.create properly?

unsure ya, I mean when I run the task logs do not get outputted into the clearml platform

any ideas?

so that it takes the auto logging but still able to run the with the previous specifications

got it sweet, so I need to use Task.create to run on custom containers... so would the workaround here running Task.create and then running Task.init(continue_last_task=task.id) ?

SmugDolphin23 so I ran that above like
` task = Task.init(project_name=project, task_name='data_upload')
task.set_base_docker(
docker_image="nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04",
docker_arguments=docker_args,
)

task.execute_remotely(queue) `and it works good, except there still does not seem to be autologging or even capturing print statements on the remote execution

no longer using the create.

got it will try