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12 × Eureka!so that it takes the auto logging but still able to run the with the previous specifications
hm SmugDolphin23 so I added this into the Task but I still do not get auto logging for a pytorch training task
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
unsure ya, I mean when I run the task logs do not get outputted into the clearml platform
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
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
so curious if this is just a me misuderstanding and not using the .init/.create properly?
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)
?