Any thoughts SuccessfulKoala55 ?

It failed on some missing files in my remote_execution, but otherwise seems fine now

Yeah 🤔 🤔 they did. I'll give your suggested fix a go on Monday!

True, and we plan to migrate to pipelines once we have some time for it :) but anyway that condition is flawed I believe

(in the current version, that is, we’d very much like to use them obviously :D)

Thanks AgitatedDove14 , I'll give it a try. Perhaps additional documentation is needed for that extra_layout

~20

For now we've monkey-patched it to our usecase:

` Dataset._Dataset__hidden_tag = "active"

    def foo(cls, dataset_project, dataset_name):
        dataset_project = dataset_project or "Datasets"
        return dataset_project, dataset_project.rpartition("/")[0]

    Dataset._build_hidden_project_name = foo `

Sorry, found it on my end!

Or the above;)

That's what I found as well, but it did not like it after all (boto is fine with it, but underlying urllib and requests were not?)

It's fine -- I see the added benefit in making sure the users set up their clearml.conf and I've made a script to edit it to our needs as part of the installation process 🙂 Thanks Martin!

SuccessfulKoala55 That string was autogenerated by pyhocon and matches their documentation too - https://github.com/lightbend/config/blob/master/HOCON.md#substitutions
The first example won't work (it will treat ${...} as a string literal and won't replace it). The second does work, but as mentioned anyway, these were not hand typed, but rather generated from pyhocon, so I don't think that's the issue 🤔

SuccessfulKoala55 no that did not solve the issue 😞

We have a more complicated case but I'll work around it 😄

Follow up though - can configuration objects refer to one-another internally in ClearML?

There's not much (or anything) in the log to provide...

` (.venv) 15:42 [0:user@server$~] CLEARML_CONFIG_FILE=~/agent_clearml.conf clearml-agent daemon --queue default on_prem --detached --order-fairness
Environment variables set from configuration: ['AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY', 'AWS_DEFAULT_REGION']
...

If I add the bucket to that (so CLEARML_FILES_HOST= s3://minio_ip:9000/minio/bucket ), I then get the following error instead --

2021-12-21 22:14:55,518 - clearml.storage - ERROR - Failed uploading: SSL validation failed for ... [SSL: WRONG_VERSION_NUMBER] wrong version number (_ssl.c:1076)

Honestly I wouldn't mind building the image myself, but the glue-k8s setup is missing some documentation so I'm not sure how to proceed

Sure SuccessfulKoala55 , and thanks for looking into it.

As an alternative (for now, or in general), we could consider reverting back to pip. The issue we encounter is that we have a monorepo, so frozen requirements should specify relative paths, but pip freeze does not seem to do that, so ClearML also fails in pip mode

Here's an example where poetry.lock is removed, and still the console reads:
url: .... branch: HEAD commit: 22fffaf8d5f377b7f10140e642a7f6f26b72ffaa root: /.../.clearml/venvs-builds/3.10/task_repository/... Applying uncommitted changes Poetry Enabled: Ignoring requested python packages, using repository poetry lock file! Creating virtualenv ds-platform in /.../.clearml/venvs-builds/3.10/task_repository/.../.venv Updating dependencies Resolving dependencies...

The instance that took a while to terminate (or has taken a while to disappear from the idle workers)

JitteryCoyote63 yes exactly, sorry, I forgot to add the Task.get_task in my response. That's exactly what we do 😅

Yes that's what I thought, thanks for confirming.

So a normal config file with environment variables.

(Following this)

Is there a way to accomplish this right now FrothyDog40 ? 🤔

proj_suffix = "" i = 2 while Task.get_project_id(f"{proj_name}{proj_suffix}") is not None: tasks = Task.get_tasks(project_name=f"{proj_name}{proj_suffix}") if not [task for task in tasks if not task.get_archived()]: # Empty project, we can use this one... break proj_suffix = f"_{i}" i += 1

Btw TimelyPenguin76 this should also be a good starting point:
First create the target directory and add some files:sudo mkdir /data/clearml sudo chmod 777 -R /data/clearml touch /data/clearml/foo touch /data/clearml/bar touch /data/clearml/bazThen list the files using the StorageManager. It shouldn't take more than a few miliseconds.` from clearml import StorageManager

%%timeit
StorageManager.list("/data/clearml")

-> 21.2 s ± 328 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) `

Thanks AgitatedDove14 , I'll first have to prove viability with the free version :)

can I assume these files are reused

A definite maybe, they may or may not be used, but we'd like to keep that option 🙃

Maybe the "old" way Dataset were shown is better suited ?

It was, but then it's gone now 😞

I see your point, this actually might be a "bug"?!

I would say so myself, but could be also by design..?

Awesome, I'll ask Product to reach out

LMK, happy to help out!
I know our use case is maybe a very different one, but...

That gives us the benefit of creating "local datasets" (confined to the scope of the project, do not appear in Datasets tabs, but appear as normal tasks within the project)