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

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

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

this is now in my python script:

it didn''t make a difference

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

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

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

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

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

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

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

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

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

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

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

its as if the line is not there

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

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

(same for environment variable)

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)

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

i think i found it. we had to replace elasticsearch after install of clearml. then i guess clearml migrations iddn't rerun

None

its a relatively fresh deploy

on kubernetes

i sniffed the traffic

i did this as a workaround:

curl -XPUT " None " -H 'Content-Type: application/json' -d'
{
"properties": {
"metric": { "type": "text", "fielddata": true },
"variant": { "type": "text", "fielddata": true }
}
}'

but this workaround should not be needed ,right ? is this a compat issue ? or was my elasticsearch not properly initialized ?