MuddySquid7 you mean you are creating them with TB ? or are you uploading them as debug images ?
Specifically in the ClearML UI, do you have it under "plots" tab or "debug samples" tab ?

Hi MuddySquid7 issue is verified, v1.1.1 will be released in a few hours with a fix.
Thank you for noticing!

From creating the event to actually sending it ... 30 min sounds like enough "time"...

why doesn't this happen on my other experiments?

same 100+ reports ?
(My new theory is that calling Task.reload() will fix it, and it might be called internally for the other experiments, like when reporting models/artifacts)
Could that be the case ?

So the TB issue was reported images were not logged.
We are now talking about the caching, which is actually a UI thing which clearml-server version are you using ?
And where are the images stored (the default files server or is it S3/GS etc.) ?

a bit sad that there is no working integration with one of the leading time series framework...

You mean a series darts reports ? if it does report it, where does it do so? are you suggesting we have Darts integration (which sounds like a good idea) ?

Where is darts reporting scalars ?

Anyone wants to open a github issue, so we actually end up implementing it 😉 ?

Yes, consider VexedCat68 txt file the Dataset "content" , this will enable ypu to safely get the list of files, and then you can use the StorageManager to download them extend this concept and have it built into the Dataset itself, i.e. allow you to add files as links and make sure it will just download them. The caveat here is that the Dataset at the end, returns a folder with the files, when you specify links, you have to also specify the target location locally (at the end you want a fol...

Hi ScaryLeopard77
Could that be solved with this PR?
https://github.com/allegroai/clearml/pull/548

Hi RoughTiger69
A. Yes makes total sense . Basically you can use Task.export Task.import to do achieve this process (notice we assume the dataset artifacts links are available on both, usually this is the case)

B. The easiest way would be to use Process , then one subprocess is exporting from dev , where the credentials and configuration is passed with os environment. The another subprocess imports it to the prod server (again with os environment pointing to the prod server). Make sense?

ReassuredTiger98

It seems like clearml is not able to fetch the dependencies correctly when 

importlib

 is used.

If you have an example please let me know we'll try to fix it :)

Is it possible to read the dependencies manually from a conda environment.yml?

You can set detect_with_conda_freeze: true in clearml.conf, it will just use the entire conda env
https://github.com/allegroai/clearml/blob/28b85028fe4da3ab963b69e8ac0f7feef73cfcf6/docs/clearml.conf#L170

The package is just subdir by the way. So it should not be in installed packages anyways, right?

Correct, also when the agent is spinning the code it will automatically add the root of the git repository to the pythonpath so you should be able to load the package.

I'm kind of at a point where I don't know a lot of what to even search for.

we feel you 💗 , yes there still isn't a very good source of information on where to get started...
This is because the entire field is constantly changing and evolving, and one solution will usually only apply to specific use case...
I would start with the mlops community slack channel, and youtube talks (specifically those by companies describe how they built their own internal infrastructure, i...

If that's the case you have two options:

• Create a Dataset from local/nfs and upload it to the S3 compatible NetApp storage (notice this create an immutable copy of the data)
• Create a Dataset and add "external links" to either the S3 storage with None :port/bucket/... or direct file link file:///mnt/nfs/path , notice that in this example the system does not manage the data that means that if someone deletes/moves the data you are unaware of that And of course you can...

Try this one 🙂
HyperParameterOptimizer.start_locally(...)
https://clear.ml/docs/latest/docs/references/sdk/hpo_optimization_hyperparameteroptimizer#start_locally

it seems it's following the path of the script i'm using to task.create, eg:

The folder it should run it is the script path you are passing (i.e. "script=ep_fn," )
Wrong path would imply that is it not finding the correct repository, is that the case ?

yes you are correct, I would expect the same.
Can you try manually importing pt, and maybe also moving the Task.init before darts?

Where do you have your Task.init ?

VexedCat68 make sense, we could also (if implementing this feature) add a special Tag to the dataset , so you know it contains "external" links, wdyt?

. I guess this can be built in as a feature into ClearML at some future point.

VexedCat68 you mean referencing an external link?

Yes, though the main caveat is the data is not really immutable 😞

BTW: this is probably more efficient than pickling
https://pandas.pydata.org/pandas-docs/version/1.1.5/reference/api/pandas.DataFrame.to_parquet.html

but this is not different from not using clearml-data,

ReassuredTiger98 just making sure we are on the same page. clearml-data immutability is fixed, the user cannot change the content of the dataset (it is actually compressed and uploaded). If you want to change it, you create a new child version

For reporting the console logs you can use :
logger.report_text("my log line here", print_console=False)https://github.com/allegroai/clearml/blob/b4942321340563724bc16f60ea5dd78c9161778d/clearml/logger.py#L120

ReassuredTiger98 oh wow I did not realize you actually call importlib to import your libraries (any reason not to call import ?)
And yes, I think we will miss it as the package analysis is actually static text analysts of the code

I will create a minimal example.

Many thanks ReassuredTiger98 !

ReassuredTiger98 I can verify the code snippet reproduces the issues with packages missing from "installed package".
If you feel this is important, please open a GitHub issue.
Also, you can manually add packages:
Task.add_requirements('package_name_here', 'optional version here')
So when you manually load the package you can make sure it will be listed, do remember to call it before the Task.init call.

What's the "working dir" ? (where in the repo the script is executed from)

Hi CluelessElephant89

Hi guys, if I spot issue with documentations, where should I post them?

The best way from our perspective PR the fix 🙂 this is why we put it on GitHub