EagerOctopus10

I did, but I only find task name, I'm looking to filter by the project

Is tehre anything specific about the logs we're looking for? Because if I just dumop them it will take me a while to see no sensitive data and naming is there

I restarted the server and it works now

e.g. docker-compose restart

For me a simple restart worked

AgitatedDove14 permanent. I want to start with a CLI interface that allows me add users to the trains server

I'll try

a third one?

I'll check the version tomorrow, about the current_task call, I tried before and after - same result

Continuing on this discussion... What is the relationship between configuring files_server and all the rest we just talked about and the the default_output_uri ?

I'm using ip address show

How do I get from the node to the task object?

Clicking on that link exaclty 🙂

AgitatedDove14 UnevenDolphin73

I'm using iteration = 0 at the moment, and I "choose" the max and it shows as a column... But the column is not the scalar name (because it cuts it and puts the > sign to signal max).

For the sake of comparing and sorting, it makes sense to log a scalar with a given name without the iteration dimension

Increased to 20, lets see how long will it last 🙂

CostlyOstrich36 so why 1000:1000? My user and group are not that and so do all the otehr files I have under /opt/clearml

SuccessfulKoala55 AppetizingMouse58

[ec2-user@ip-10-0-0-95 ~]$ df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 3.9G 0 3.9G 0% /dev tmpfs 3.9G 0 3.9G 0% /dev/shm tmpfs 3.9G 880K 3.9G 1% /run tmpfs 3.9G 0 3.9G 0% /sys/fs/cgroup /dev/nvme0n1p1 8.0G 6.5G 1.5G 82% / tmpfs 790M 0 790M 0% /run/user/1000

what should I paste here to diagnose it?

I mean, I barely have 20 experiments

Hahahah thanks for the help SuccessfulKoala55 & CostlyOstrich36

I really do feel it would be a nice to have the ability to easily configure the Cleanup Service to cleanup only specific projects / tasks as its a common use case to have a project dedicated for debugging and alike

moreover I think I found a bug

Yes, I have a metric I want to monitor so I will be able to sort my experiments by it. It is logged in this manner

logger.report_scalar(title='Mean Top 4 Accuracy', series=ARGS.model, iteration=0, value=results['top_4_acc'].mean())
When looking at my dashboard this is how it looks

only string

see gif:

Could be, my message is that in general, the ability to attach a named scalar (without iteration/series dimension) to an experiment is valuable and basic when looking to track a metric over different experiments

it is a model name

Nope

That is not very informative