DepressedChimpanzee34 Have you noticed the "Show n experiments selected" button on the bottom bar? This effectively toggles your view between whatever is currently sorted/filtered and the current item selection.
To address the scenario you describe: Switch to "Show selected experiments", remove the redundant items, and switch back to the original view: "Show all experiments"
Thoughts?
DepressedChimpanzee34 ClearML tries to conserve storage by limiting the history length for debug images (see sdk.metrics.file_history_size https://clear.ml/docs/latest/docs/configs/clearml_conf#sdk-section ), though the history can indeed grow large by setting a large value or using a metric/variant naming scheme to circumvent this limit.
Does your use case call for accessing a specific iteration for all images or when looking at a specific image? Note that the debug image viewer (wh...
@<1523706095791509504:profile|FiercePenguin76> The "Log" tab has been renamed "Console" in ClearML 0.17.0 - Thanks for pointing out the outdated description.
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.
UpsetTurkey67 The single set of online documentation ( https://clear.ml/docs/latest/docs ), denotes OSS/Free-SaaS/Paid features as such. For example: https://clear.ml/docs/latest/docs/configs/clearml_conf#configuration-vault
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
MelancholyElk85 Thanks for calling this to attention. What do you think would have made it easier for you to notice the available extended list content?
I would assume that a "type to match" option would also have helped?
Appreciate if you could https://github.com/allegroai/clearml/issues/new/choose so this can be pushed forward.
SmarmySeaurchin8 Following up on ColossalDeer61 's hint, notice https://allegroai-trains.slack.com/archives/CTK20V944/p1597248476076700?thread_ts=1597248298.075500&cid=CTK20V944 not-too-old thread on reusing globally installed packages.
Hi HealthyStarfish45 ,
Since you're discussing the experiment list, I assume that by "fixed view per experiment" you actually mean "per project" (as the list view is across all experiments in the list)?
Under this assumption, note that the view configuration (column sort, custom columns, filters) is also specified in the browser URL. So, until the Trains UI supports in-app per-project view preferences - You can simply bookmark the URL.
Does this help?
@<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.
UnsightlySeagull42 The upgrade process is slightly different depending on the environment in which you've deployed your ClearML server (e.g. for a https://allegro.ai/clearml/docs/docs/deploying_clearml/clearml_server_linux_mac.html#upgrading ).
Note the document you are referring to only applies once when you're moving from the older pre-0.16 versions in which case DB migration is required.
If your server is more up to date (0.16 and newer) you should be OK with the link above.
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...
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...
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?
CooperativeSealion8 For future reference, notice there's a configuration reference available at https://allegro.ai/docs/references/trains_ref/
BattyLion34 Adding to AgitatedDove14 hint. See the following docs page: https://allegro.ai/clearml/docs/docs/deploying_clearml/clearml_config_for_clearml_server.html
KindGiraffe71 Have you checked out the https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch-lightning/pytorch_lightning_example.py ? https://clearml.slack.com/archives/CTK20V944/p1616070536033700 previous discussion provides some insight into how it works under the hood.
WittyOwl57 Is that information available for you on each of the compared experiments when you view them individually?
WittyOwl57 No worries 🙂 happens to the best!
WittyOwl57 The UI shows repo and package detailed comparison under the "Details"/"Execution" (See sample screenshot), whereas auto-logged environment variables are shown under the "HyperParameters" comparison tab.
What do you find missing beyond those?
WittyOwl57 I just used a couple of the experiments in the https://app.community.clear.ml/projects/764d8edf41474d77ad671db74583528d/ of the free tier server.
TightElk12 This makes a lot of sense - should make it into one of the coming releases
JitteryCoyote63 Great idea. Appreciate if you https://github.com/allegroai/clearml/issues/new/choose .
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
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 :)
DepressedChimpanzee34 Always appreciated
Thanks for noticing @<1523708920831414272:profile|SuperficialDolphin93> - ClearML is already there under it's legacy "Trains" name, it's indeed past time for an update.