WickedGoat98 Nice!!!
BTW: The fix should solve both (i.e. no need to manually cast), I'll make sure the fix is on GitHub so you'll be able to verify 🙂

Hi DisgustedDove53

Now for the clearml-session tasks, a port-forward should be done each time if I need to access the Jupyter notebook UI for example.

So basically this is why the k8s glue has --ports-mode.
Essentially you setup a k8s service (doing the ingest TCP ports) then the template.yaml that is used by the k8s glue should specify said service. Then the clearml-session knows how to access the actual pod, by a the parameters the k8s glue sets on the Task.
Make sense ?

Hi @<1544853721739956224:profile|QuizzicalFox36>
Sure just change the ports on the docker compose

You cannot call exit(0) and kill the kernel from the SageMake notebook

Hi RipeGoose2
Just to clarify, the issue with the html stuck in cache is a UI, thing, basically the webapp needs to tell the browser not to cache the artifacts, it has nothing to do with how the artifacts are created.
Regardless we love improvements so feel free to mass around with the code and PR once you get something useful 😉
Specifically this is where the html conversion happens
https://github.com/allegroai/clearml/blob/9d108d855f784e1fe7f5691d3b7bf3be64576218/clearml/backend_in...

👍

Hi NonsensicalSeaanemone47
I'm assuming you mean k8s as compute cluster?
If so, then yes clearml adds priority scheduling on top of your existing kl8s cluster. It also allows you to reuse images as the k8s spins the base container image and then inside the container image the agent sets the environment of the experiment (clones code, apply diff, install missing python packages etc.)
It also gives visibility into the executed pods.
Make sense ?

Is there a helper function option at all that means you can flush the clearml-agent working space automatically, or by command?

Every Task execution the agent clears the venv (packages are cached locally, but the actual venv is cleared). If you want you can turn on the venv cache, but there is no need to manually clear the agent's cache.

Hi TrickySheep9
It should filter only "published" if required, this is the "ready" flag

you mean "/home/user/local_storage_path" does not exist ?

So basically a list of Path objects ?

Yey!
My pleasure 🙂

Hi MagnificentSeaurchin79
This sounds like a deeper bug (of a sort), I think the best approach is to open a GitHub issue with some code that can reproduce this behavior, or at least enough information so that we could try to catch the bug.
This way we will make sure it is not forgotten.
Sounds good ?

what's the docker version?

ElegantCoyote26 I don't think Keras logs it anywhere unless you have TB, so nowhere to take the data from...
In short, yes you have to have TB :)

So if everything works you should see "my_package" package in the "installed packages"
the assumption is that if you do:
pip install "my_package"
It will set "pandas" as one of its dependencies, and pip will automatically pull pandas as well.
That way we do not list the entire venv you are running on, just the packages/versions you are using, and we let pip sort the dependencies when installing with the agent
Make sense ?

We already redesigned the implementation so it should be quite easy to extend to GCP and Azure, what are you planning ?

does that mean that it will install my package lastly?

It will install last, but not because it was last in the list, but because it is local/repo package 🙂

Can I do in setup.py the modifications to the tensorflow code?

You mean like have the changes as part of the "uncommitted changes" section ?

This is only in the preview right ?

Will the new fix avoid this issue and does it still requires the 

incremental

 flag?

It will avoid the issue, meaning even when incremental is not specified, it will work
That said the issue any other logger will be cleared as well, so, just good practice ...

From the 

logging

 documentation ...

Hmmm so I guess Kedro should not use dictConfig ?! I'm not sure on the exact use case, but just clearing all loggers seems like a harsh approach

artifact I guess

Ohh ignore the YAML

Queues can have multiple workers, and that implies multiple instances of a task can run concurrently.

@<1533619716533260288:profile|SmallPigeon24> as long as these are the Exact same instances you can have them runing simultaneously (think multi node training), that said each one should "know" not to report over the others, because of course it will overwrite the reports.

Back to your point on multiple agents:
You cannot have two Tasks in the same queue, that means that a single agen...

I’ll check if I could wrap the code in something that calls the Task.delete if debugging

Whatever you think works best for you, I was genuinely curious 🙂
To me (personally) it is helpful to have a log even while debugging (comparing to previous runs etc, trying to see what went wrong even on a console output level). When I'm done I just search for everything I worked on select all, and archive them. Then a cleanup service in the background clears all the archived Tasks once they ar...

Hmm, it seems as if the task.set_initial_iteration(0) is ignored...
What's the clearml version you are using ?
Is it the same one you have on the local machine ?

Correct (with the port mapping service in it)

Yes 🙂 documentation is being worked on ... Anyhow we will be uploading a new documentation site soon (hopefully in a week or so), putting it all on GitHub so it will be easier for the community to edit and add more

This is awesome, thank you!

But functionality is working

Awesome , I will wait with the merge until tested internally .
There is a resale coming out after the weekend, once it is out I expect we will merge it.

PleasantGiraffe85 you can disable the SSL verification on the client end:
https://github.com/allegroai/clearml-agent/blob/21c4857795e6392a848b296ceb5480aca5f98e4b/docs/clearml.conf#L12
Basically you can just manually create the clearml.comf with only the following:
api { api_server: web_server: files_server: `
credentials {"access_key": "EGRTCO8JMSIGI6S39GTP43NFWXDQOW", "secret_key": "x!XTov_G-#vspE*Y(h$Anm&DIc5Ou-F)jsl$PdOyj5wG1&E!Z8"}

# verify...