I updated my clearml-server, but the issue is still present

Thanks! Version: 1.1.1-135 • 1.1.1 • 2.14

I am very confused now, I tried switch to my local machine and change the clearml.conf.
It only partly worked :
Dataset.list_datasets() returns the correct list (from the remote server).
But Dataset.get(dataset_id="ce2abe847e004ac282cc435bfa9c4bd5")
gives me :
2021-12-20 13:46:39,404 - clearml.storage - ERROR - Could not download ` , err: Failed getting object localhost:8081/annotation_dataset/annotation.ce2abe847e004ac282cc435bfa9c4bd5/artifacts/state/state.json (404): <!DO...

What is the proper way to change a clearml.conf ?

The URLs are correct, I can use them to download the dataset zip.

Okey thank you!
If I plan using S3 for external file storage, do I still need Elasticsearch and Mongo ?

The logs continue like this :
` Summary - installed python packages:
pip:

• attrs==20.3.0
• backports.entry-points-selectable==1.1.1
• certifi==2021.10.8
• chardet==4.0.0
• clearml==1.1.4
• Cython==0.29.26
• distlib==0.3.4
• filelock==3.4.0
• furl==2.1.3
• future==0.18.2
• idna==2.10
• jsonschema==3.2.0
• numpy==1.21.5
• orderedmultidict==1.0.1
• pathlib2==2.3.6
• Pillow==8.4.0
• platformdirs==2.4.0
• psutil==5.8.0
• pyhocon==0.3.59
• PyJWT==2.0.1
• pyparsing==2.4.7
• pyrsistent==0.18.0
• pyt...

Ah! That's it, thank you very much ! I did not know this was an issue. I though the dataset was only linked to the fileserver and not to the specific url used to upload it.

Okey thanks!

Maybe it is some sort of misunderstanding from my side ? I thought :
Task.enqueue(task, queue_name="training_queue")is what starts the execution of the task. Do I need another function ?

It seems the agent does not like working with scripts located inside a git repository, I moved the requirements and the script in a folder without a .git and it works now, thank you!

here is the command I am using :
sudo docker run -it -v /home/ubuntu/app/:/app/ -v /home/ubuntu/folder/clearml.conf:/root/clearml.conf --network "clearml_backend" my_image bash

CostlyOstrich36 Yes, I am getting the exact same error as Malcolm (thanks for the link!) except I can see the URLs of my artifacts instead of undefined .
SuccessfulKoala55 I am running a self-hosted server. I installed it about 3 months ago, so I would assume my current version is v1.1.1 , how can I check for sure ?

The fileserver is remote, but the bandwidth is not an issue.
Is the automatic artifact storage of clearml async ? (meaning even if the task is finished it could still be uploading associated artifacts ?)

Is there a way to make it synchronous ?

I don't really know. I just detected it automatically from the start, so I haven't looked into it yet.

Thank you! Is there a way to test the agent on a machine without GPU ?
When running this little script, I can see my agent installing the requirements, but it does not seem to ever start running the task.
task = Task.create( project_name="train", task_name="train", requirements_file="./requirements.txt", repo="") task.set_script(entry_point="./test.py") Task.enqueue(task, queue_name="training_queue")The logs are as follows :
` Starting Task ...

For example to create a dataset, I use this :
from clearml import Dataset ds = Dataset.create(dataset_project='XX', dataset_name='XX') ds.add_files( path='/tmp/tmpbk2g6c3h' ) ds.upload() ds.finalize()

Python 3.8.12

I can provide a screenshot, but I'd need to hide the urls 😅 and if do so it would look just like Malcolm's screenshot.

I did, I copy pasted the config from within the docker

of course, I am checking using the env command

Okey thanks! I'll try this, if it does not work I'll just deactivate the automatic detection feature.

there is nothing in the env

I was looking at the code of the Dataset class, but I could not find where the files_server is retrieved.

If it helps, I tried changing the python version to 3.9 (which is also installed in my image). The change is reflected in the agent's config (the lines that appear when starting the worker) but it's still using 3.8 when executing the script.

I noticed logs start as follows :
/usr/bin/python3.9 /usr/bin/python3.9: No module named pip /usr/local/bin/python3.8

Sorry for the late reply. It is indeed a venv, I though it would not be an issue since the PYTHONPATH and the PATH are both set to prioritize the venv. I'll try to create a more classic image.

even thought when starting the worker I see this :
agent.python_binary = /opt/venv/bin/python3