Thanks letting us know @<1784392065820397568:profile|SplendidFox3> - The signup for app.clear.ml had indeed broken down, but we should be back on track - Can you now complete the registration?

RotundHedgehog76 Have you tried clearml-data add --files .
? (Probably best to try on a smaller subset first)

GreasyPenguin14 That's an annoying bug indeed - Thanks for spotting it. If you need to circumvent it before a fix comes out in one of the near releases, you can programatically use the https://clear.ml/docs/latest/docs/references/api/endpoints#post-projectsupdate e.g.
from clearml.backend_api.session.client import APIClient client = APIClient() client.projects.update(project='<project ID>', description='My new description')
Note you can get your project's ID either from the webapp URL...

Thanks for clarifying @<1523705301990117376:profile|WickedCat12> .
As I mentioned originally, plotting an arbitrary metric against another is further down the ClearML roadmap.
It'd be great if you use a github issue to help push it through :)

@<1523706095791509504:profile|FiercePenguin76> The "Log" tab has been renamed "Console" in ClearML 0.17.0 - Thanks for pointing out the outdated description.

TightElk12 This makes a lot of sense - should make it into one of the coming releases

DepressedChimpanzee34 Apologies for missing your previous comment.
Totally agree that the global selection indicator should maintain its 'clear selection' behaviour even if some/all of the selection is off-screen.

GreasyPenguin14 When the project description is empty you get a "Add project overview" instead if the "Edit" button:

@<1523709410411548672:profile|NuttyFox2> Since the default server user configuration does not require authentication, I'm assuming your use case calls for some users being authenticated where others are not?
Such mixed access mode is currently not on the near term roadmap for the OSS server - You should create a feature request to help push it into the development plan.

Hi DefeatedCrab47 ,
The examples folder has just been restructured: Find the example here:
https://github.com/allegroai/trains/blob/master/examples/services/hyper-parameter-optimization/hyper_parameter_optimizer.py

There's an example here to get you going @<1645597514990096384:profile|GrievingFish90> .
We'll definitely look into finding a place for this info in the ClearML docs.

ExcitedFish86 You can https://clear.ml/docs/latest/docs/webapp/webapp_exp_table#adding-metrics-and--or-hyperparameters to include any parameter/metric column that helps your analysis (and subsequently filter the table on those columns).
There's not yet the equivalent of a parameter importance visualization, though such insight visualizations are definitely in our sights.
Sure appreciate if you can https://github.com/allegroai/clearml/issues/new on the subject :)

UnevenDolphin73 Am I missing anything in rephrasing your use case to "Have a single autoscaler service multiple queues" (where the autoscaler resource configuration is, in essence, the pool you mention)?

@<1523705301990117376:profile|WickedCat12> ClearML Scalars explicitly show metrics time progression (you can display iteration/wall-time).
Plotting one metric against another is a feature that lies further down ClearML's roadmap.

If your metric is reported only once per epoch you can make use of the existing scalars functionality by making use of the iteration parameter when reporting your metric to reflect the epoch instead.

Does this make sense?

DepressedChimpanzee34
a filter similar to one in the scalars page where you can display a subset of the reported debug images can be usefulThe scalars page provides a metric hide/show control - Is this the one you mean? The debug images page also provides a filter by metric - Depending on your naming policy this can easily be used to focus on more sparsely appearing images.
Else, an example of the filter you were thinking of would be appreciated.

Regardless, direct iteration access cou...

MysteriousBee56 would providing Trains with an "import mode" (say, via environment or command line variable), which means that it should create a draft server entry, populate all the execution/environment info and exit before it actually starts employing the ML infrastructure address your use case?

DefeatedCrab47 Happy you're finding Trains useful 🙂

but it definitely has it's advantages if TRAINS would support it (early stage Data Science infrastructure).

No doubt, and I definitely see such usable example in the cards for Trains' upcoming versions...

HappyDove3 Notice that in https://github.com/allegroai/clearml/issues/400 the goal is to see a table plot in the UI scalars tab for a specific experiment (with additional discussions on how these will be addressed when comparing experiments).
Note that once you take the approach you suggested of logging your metrics single values, you can configure your experiment comparison scalars view to show single values instead of the time-series graph which I think will provide you with the matrix c...

ScrawnyLion96 Looks like a case of broken links - Check out https://clear.ml/docs/latest/docs/references/api/definitions#tasksexecution and https://clear.ml/docs/latest/docs/references/api/definitions#tasksconfiguration_item

WittyOwl57 Is that information available for you on each of the compared experiments when you view them individually?

JitteryCoyote63 Great idea. Appreciate if you https://github.com/allegroai/clearml/issues/new/choose .

Hi JuicyOtter4
The GUI search returns all experiments in the project that have your search string in their task id, name, description or any of their models' names.
You can use regex with the '.*' button in the search bar.

JitteryCoyote63 Not currently there, but certainly sounds like something to add to the list - Care to https://github.com/allegroai/clearml/issues/new/choose ?

@<1628927672681762816:profile|GreasyKitten62> When you have specific display considerations, you can implement them through report_table's 'extra_layout' and 'extra_data' parameters

HappyDove3 you can get some more insight on the different configuration methods and how to use theme https://clear.ml/docs/latest/docs/fundamentals/hyperparameters

DepressedChimpanzee34 Always appreciated

WittyOwl57 No worries 🙂 happens to the best!

DefeatedCrab47 For the most part, mlflow can serve basic ML models using scikit-learn. In contrast, Trains was designed with more general purpose ML/DL workflows in mind, for which there's no "generic" way to serve models as different scenarios can use different input encoding, models results would be represented in a variety of forms, etc.
Consider also, that creating an HTTP endpoint for model inference is quite a breeze: there are multiple examples of Flask on top of any DL/ML framework w...

WittyOwl57 I just used a couple of the experiments in the https://app.community.clear.ml/projects/764d8edf41474d77ad671db74583528d/ of the free tier server.

DepressedChimpanzee34 Experience has shown that some mechanisms for mitigating large sets impact on browser performance are required.
Your 2nd suggestion for adding an in-app search tool for such sections seems to be completely in line with ClearML's behaviour in other UI sections (e.g. console logs) - It'd be great if you can https://github.com/allegroai/clearml/issues/new/choose