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

any ideas?

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

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

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

got it will try

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) ?

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

no longer using the create.

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

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

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