BTW
Grafana Visualizing endpoint request latency as well as prediction result value distributions

I think it is free 🙂 (registration that is)

🤞

DefeatedCrab47 link is fixed :)

Thank you! 😍

Hi @<1578918150261444608:profile|RoundJellyfish71>
Yes it can, there check these examples:
None
None

I located the issue, I'm assuming the fix will be in the next RC 🙂
(probably tomorrow or before the weekend)

Hi VirtuousFish83 ,
Is it throwing an exception? Are you seeing the plot in the UI but the title is incorrect?

Thanks VirtuousFish83 !
This is great

FrustratingWalrus87 Unfortunately TB's TSNE is not automatically captured by ClearML (Scalars, histograms etc. are)
That said, matplotlib will be automatically captured do you can run your own PCA/tSNE and use matplotlib to visualize (ClearML will capture it).
The same applies for plotly.
What do you think?

Hi WittyOwl57

I'm guessing clearml is trying to unify the histograms for each iteration, but the result is in this case not useful.

I think you are correct, the TB histograms are actually a 3d histograms (i.e. 2d histograms over time, which would be the default for kernel;/bias etc.)

is there a way to ungroup the result by iteration, and, is it possible to group it by something else (e.g. the tags of the two plots displayed below side by side).

Can you provide a toy example...

I'll make sure we look into it

Hi SkinnyPanda43
Can you attache the full log?
Clearml agent is installed before your requirements.txt , at least in theory it should not collide

Hi UpsetBlackbird87
This is an Optuna decision on how many concurrent tests to run simultaneously.
You limited it to 100, but remember Optuna does a Bayesian optimization process, where it decides on the best set of arguments based on the performance of the previous set, this means it will first try X trials, then decide on the next batch.
That said you can a pruner to Optuna specifying how it should start
https://optuna.readthedocs.io/en/v1.4.0/reference/pruners.html#optuna.pruners.Median...

Hi AverageBee39
It seems the json is corrupted, could that be ?

Nice catch AverageBee39 🙂

And actually the slack thing is actually a good workaround this since people can just comment easily

Any reference for similar integration between Slack and other platforms ?
I'm thinking maybe the easiest way is Slack bot to you can @ task id ?

I understand but how do you launch the cleaml-agent itself:
clearml-agent daemon --detached --queue default --docker

Seems like settings on the clearml-server disappeared (specifically default queue tag?!)

in the docker-compose file. Still strange...

hmm yes it is... If you have an idea on what went wrong let me know, we would love to fix it

Could you send the "installed packages" section of the Task that was created in the notebook ?

Thanks CooperativeFox72 ! I'll test and keep you posted 🙂

HurtWoodpecker30 in order to have the venv cache activated, it uses the full "pip freeze" it stores on the "installed packages", this means that when you cloned a Task that was already executed, you will see it is using the cached venv.
(BTW: the packages themselves are cached locally, meaning no time is spent on downloading just on installing, but this is also time consuming, hence the full venv cache feature).
Make sense ?

So net-net does this mean it’s behaving as expected,

It is as expected.
If no "Installed Packages" are listed, then it cannot pull a cached venv (because requirements.txt is not a full env, and it never analyzed it)).
It does however create a venv cache based on it (after installing it)
The Clone of this Task (i.e. right click on the UI clone experiment, enqueue it, Will use the cached copy becuase the full packages are listed in the "Installed Packages" section of the Task.
Make sens...

well it should fail, but I think the error message should be fixed 🙂
maybe:
ValueError: dataset 'tmp_datset' not found in projectlavi-testing' `wdyt?

Hmm
CLEARML_CUSTOM_BUILD_OUTPUT
This might be an enterprise feature, I'm not aware of anything in the open source version

Even if you had any packages, I'm pretty sure there is nothing for you to worry about, it will just list them, and if they are preinstalled, the preinstalled will be used

If this is the case, there is nothing you need to change, just provide the docker image (no need to pass packages )

PompousParrot44 with pleasure. If during your search for a solution you come across something that solves it, and might integrate to the agent, do not hesitate to suggest it :)

PompousParrot44 now that I think about it, you might be able to limit the cpu affinity, would that help?