if you go here https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_aws_ec2_ami you can see you can launch a community ami and if you go here https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_aws_ec2_ami/#clearml-server-aws-community-amis you will see the list of community AMI’s you can launch

you can use Task.update_output_model() to update the name of the output moel

from the clearml logs when setting up the clearml server using kubernetes

i'm looking at the server.py file and it doesn't have call = self. create_api_call(request)

bugs i understand are better than ones i dont lol

i think the call is wrong

sure where do i patch it?

i would greatly appreciate that!

not sure if it will work but its worth a try

SuccessfulKoala55 do you mean request_handlers.py

should it be http://log.info (...)

` [2022-08-18 20:58:49,892] [9] [INFO] [clearml.request_handlers] GET
[2022-08-18 20:58:49,895] [9] [INFO] [clearml.request_handlers] Basic NUtORklQWUIzM0tIVUFRNUI4SkM6eU4yUXE4RTNvWDlpYlBRVmF1NEpiQXZQMHlUdHozNUluZVY4ZkpuZXNTRnRYbmRlR3I=
[2022-08-18 20:58:49,904] [9] [INFO] [clearml.service_repo] Returned 200 for auth.login in 6ms
[2022-08-18 20:58:50,059] [9] [INFO] [clearml.request_handlers] GET
[2022-08-18 20:58:50,060] [9] [INFO] [clearml.request_handlers] Basic NUtORklQWUIzM0tIVUFRNUI4SkM...

Failed processing request http://localhost:8008/auth.login : 'Logger' object is not callable

None

The only difference that i notice is that when i run it locally the task is completed

^ it works if i do that and use the jupyter credentials from my work space settings.

Name: clearml
Version: 1.9.1

%env CLEARML_WEB_HOST={-----}
%env CLEARML_API_HOST={-----}
%env CLEARML_FILES_HOST=undefined
%env CLEARML_API_ACCESS_KEY={-----}
%env CLEARML_API_SECRET_KEY={-----}

@<1523701070390366208:profile|CostlyOstrich36> maybe cause sagemaker is running in headless mode

but none the less I’ll continue with this work around thanks!

yeah

https://clear.ml/docs/latest/docs/configs/clearml_conf/

and when i’m running it in sagemaker

you can try to update the clearml.conf it has agent.cuda_version

model*

alternatively you could create a new OutputModel like here: https://github.com/allegroai/clearml/blob/master/examples/reporting/model_reporting.py , not sure if there is a way to stop the automatic uploading

https://clear.ml/docs/latest/docs/references/sdk/task#update_output_model