The following command should give you something:
docker logs --follow clearml-elastic

Hi @<1793451774179282944:profile|TestyMouse38> , not sure I understand, can you please elaborate?

Hi ShaggySquirrel23 , is this package inside some artifactory?

The agent needs access to the package while running, you need to have it accessible somehow on a remote machine as well. What is your setup?

There is literally 

Models

 tab in each project

Was about to mention it 😛

look like I created a new task for every epoch ...

What do you mean?

Either that or have a shared mount between the machines

WackyRabbit7 , how did you report the table? Can you please provide an example for the data structure of the table?

BattyDove56 , that was my suspicion as well, that's why I wanted to see the logs 🙂

Hi WorriedRabbit94 , what do you see in the execution section of the experiment when you run it locally?

ClearML should be backwards compatible - any combination will work. However it's always suggested to use the latest versions 🙂

Also, I think that maybe there is a bug with the CPU mode: I tried to run tests with instance without GPU , marked the option "Run in CPU mode (no gpus)" and I saw on the experiment logs that its trying to run the docker with "--gpus all" option and failed right after the execution.

Which instance type did you use?

Can you please add the full log of the execution?

MelancholyElk85 , you can specify the uri for that in your ~/clearml.conf file under sdk.development.default_output_uri

Please note that you don't provide target storage for InputModel since it's an input, and can be used only as an existing object in the system 🙂

I think output_uri=True would also work

You can use the API to call tasks.get_by_id and get that specific information. In the response it sits in
data.tasks.0.completed

Hi @<1714451225295982592:profile|FreshWoodpecker88> , is it possible that you didn't get permissions to the relevant directories to act as the actual storage for mongodb?

Hi @<1546303293918023680:profile|MiniatureRobin9> , can you attach a screenshot of what is happening?

Please do 🙂

Hi CrabbyKoala94 ,

Can you please open developer tools and see if you get some sort of error there?

VexedCat68 I think this will be right up your alley 🙂
https://github.com/allegroai/clearml/blob/master/examples/reporting/hyper_parameters.py#L43

BrightMosquito10 simply re-run it with the new version 🙂

Hi @<1557537273090674688:profile|ThankfulOx54> , HyperDatasets are part of the Scale & Enterprise licenses. You can see more here: None

In the UI you can add 'parent' column and filter by parent

Hi DrabCockroach54 , in the open source version there are no roles. You can set up users & passwords using this:
https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_config/#web-login-authentication

I am not sure there is a simple way to delete users - I think you would need to edit MongoDB manually, which I would not recommend

Hi UpsetSheep55 ,

Permissions feature is indeed exists only in the enterprise version. There are no examples for this since this an enterprise only feature.

How did you add the parameters to the pipeline? Did you refer to this example?
None

Hi IrritableJellyfish76 , it looks like you need to create the services queue in the system. You can do it directly through the UI by going to Workers & Queues -> Queues -> New Queue

Hi @<1691258549901987840:profile|PoisedDove36> , did you do all the db migrations during the upgrade or did you go straight to 1.5 form 1.0?

Yep, the setup should be very similar to minio

JitteryCoyote63 , I'm afraid currently not and only available in docker mode.

What do you need it for if I may ask?

Hi Danil,
You can use the following env variable to set it 🙂
CLEARML_AGENT_SKIP_PIP_VENV_INSTALL