but i still think the same should be possible using the Task.init

and also, on the tutorials that do something with task.init, the example always talks about running locally and not in the agent

task = Task.init(project_name='examples', task_name='moemwap', output_uri=True, reuse_last_task_id=False)

its as if the line is not there

and ... clearml-agent takes a --project and a --name argument that are mandatory , so these are never taken from Task.init

...I'm not sure I follow, the clearml-task is designed to always be used so that at the end the agent will be running the Task. What am I missing?

for comparison: this is when i use --output-uri

it seems that whatever i pass to Task.init is ignored

it was to test if reuse_last_task_id made any effect (i have the impression it doesn't)

i set reuse_last_task_id to false to force creation of a new task in all cases

it didn''t make a difference

i added --skip-task-init too

the model has this information ... the /tmp seem local URIs suggesting that it doesn't even try to upload them

and when i try to use --output-uri i can't pass true because obviously i can't pass a boolean only strings

this is now in my python script:

no i don't think so, i think rather Task.init is only used for running outside of agent

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)

this is the script shown by clearML ui. so the task.init call looks right

AgitatedDove14 your trick seems to work (i had to change the url to reflect the fact i run on k8s)

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

well it made a difference (the code for the init() is not added anymore) but it still didn't take my output uri

and if you add --skip-task-init ?
I think what happens is that the clearml-Task, adds a Task.init call without the output_uri that is called before "your" Task.init, and this is what causes it to be ignored. Could that be the case?

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

AntsyElk37

and when i try to use --output-uri i can't pass true because obviously i can't pass a boolean only strings

hmm, that sounds right, I think we should fix that so when using --output-uri true the value that is passed is actually True, not the string "true".
Regrading the issue itself:
are you saying --skip-task-init is being ignored ? and it always adds the Task.init call? you can also pass --output-uri https://files.clear.ml (which is the same as True) , does that work?

so it seems that it takes output_uri from the clearml commandline but not from the Task.init inside the scripot

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

well it doesn't fail. but whatever i set gets ignored

but i still think the same should be possible using the Task.init

This is the part the I find confusing:
Task.init(..., output_uri=True) is working for me, what is that setup that caused this line to "fail"?

(same for environment variable)