Thank you for giving me the advice @<1523701087100473344:profile|SuccessfulKoala55> @<1523701205467926528:profile|AgitatedDove14> !!

this is my client side’s clearml.conf file
I think it is almost similar with agent’s clearml.conf file

Thank you for your advice @<1523701087100473344:profile|SuccessfulKoala55>
I am really appreciate it.

Thank you for your advice!
I will change the s3 bucket that does not have a dot and try again.

after restarting the docker-compose, then another error appeared

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[6], line 1
----> 1 StorageManager.list("

")

File ~/.clearml/venvs-builds.2/3.8/lib/python3.8/site-packages/clearml/storage/manager.py:452, in StorageManager.list(cls, remote_url, return_full_path, with_metadata)
    430 @classmethod
    431 def list(cls...

here is the key/secret

sdk {
    aws {
        s3 {
            region: "ap-northeast-2"
            use_credentials_chain: false
            extra_args: {}
            credentials: [
                {
                    bucket: "

"
                    key: "S3_KEY"
                    secret: "S3_SECRET"
                }
            ]
        }
    }
}

@<1523701087100473344:profile|SuccessfulKoala55> I changed s3 bucket name None , but still has same error above.

here is a full clearml.conf file

And this is the HPO’s configuration info

Thank you for giving me the advice.

To answer your question, here is my workflow.

First, I create the task by running the below code

python3 train.py config object_detection.yaml

And in the same docker image, I run the below command to executing an agent

clearml-agent daemon --queue default --forground

After that, use this task id created above, I run the code I shared clearml_hyper.py

So I think argparser arguments are injected in the task itself before HPO

here is the full log of the failed task

and this is the Nanodet modified train code

Yes, in the train.py, I put the task.init

And this is the task configuration info