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27 × Eureka!no i don't think so, i think rather Task.init is only used for running outside of agent
don't know.. but i see for instance when using clearml-task i can put any (even nonsensical) values in Task.init
this is now in my python script:
and also, on the tutorials that do something with task.init, the example always talks about running locally and not in the agent
the model has this information ... the /tmp seem local URIs suggesting that it doesn't even try to upload them
i can pass any crazy value i want.. it doesn't matter. however, i can use --output_uri= s3://blabla and then at least i get the error that it cannot use that bucket
it seems that whatever i pass to Task.init is ignored
AgitatedDove14 your trick seems to work (i had to change the url to reflect the fact i run on k8s)
so it seems that it takes output_uri from the clearml commandline but not from the Task.init inside the scripot
this is the output of the training. it doens't try to upload (note that this is my second try so it already found a model with that name, but on my first try it didn't work either)
it was to test if reuse_last_task_id made any effect (i have the impression it doesn't)
hello, i'm still not able to save clearml models. They are generated and registered okay, but they are not on the fileserver. i now have Task.init(output_uri=True) and i also have --skip-task-init in clearml commandline so that it doesn't overwrite the task.init call
(same for environment variable)
task = Task.init(project_name='examples', task_name='moemwap', output_uri=True, reuse_last_task_id=False)
well it doesn't fail. but whatever i set gets ignored
this is my cmdline: clearml-task --name hla --requirements requirements.txt --project examples --output-uri http://clearml-fileserver:8081 --queue aws-instances --script keras_tensorboard.py
but i still think the same should be possible using the Task.init
well it made a difference (the code for the init() is not added anymore) but it still didn't take my output uri
its as if the line is not there
this is the script shown by clearML ui. so the task.init call looks right
and when i try to use --output-uri i can't pass true because obviously i can't pass a boolean only strings
i set reuse_last_task_id to false to force creation of a new task in all cases
and ... clearml-agent takes a --project and a --name argument that are mandatory , so these are never taken from Task.init
for comparison: this is when i use --output-uri