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

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

i added --skip-task-init too

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)

it didn''t make a difference

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

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

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

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

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

this is now in my python script:

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

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

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

its as if the line is not there

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 seems to be confirmed by this documentation None If you have not changed the default runtime on your GPU nodes, you must explicitly request the NVIDIA runtime by setting runtimeClassName: nvidia in the Pod spec:

hi @<1729671499981262848:profile|CooperativeKitten94> did i convince you with my argument ? do you think having runtimeClass configurable is worth it ?

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

version 7.14.4

don't know.. but i see for instance when using clearml-task i can put any (even nonsensical) values in Task.init

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

i sniffed the traffic

None

(same for environment variable)

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

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