The odd thing is that it was already defined, and then when I clicked an S3 link, it asked me to fill it in again, adding a duplicate credentials row

Sorry to keep this up - what about support for minio using the environment variable? Do I set the CLEARML_FILES_HOST to the end point instead of an s3 bucket?

Great to hear @<1523701087100473344:profile|SuccessfulKoala55> ! Is there an estimated timeline for these releases?

None, they're unusable for us.

I'm not entirely sure I understand the flow but I'll give it a go. I have two final questions:
This seems to only work for a single file (weights_path implies a single file, not multiple ones). Is that the case? Why do you see this as preferred to the dataset method we have now? 🤔

When is the next release expected? 😄

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

You don't even need to set the CLEARML_WORKER_ID, it will automatically assign one based on the machine's name

It does, but I don't want to guess the json structure (what if ClearML changes it or the folder structure it uses for offline execution?). If I do this, I'm planning a test that's reliant on ClearML implementation of offline mode, which is tangent to the unit test

Or well, because it's not geared for tests, I'm just encountering weird shit. Just calling task.close() takes a long time

This is with:
Task.set_offline_mode(True) task = Task.init(..., auto_connect_streams=False)

I'm working on the config object references 😉

Either one would be nice to have. I kinda like the instant search option, but could live with an ENTER to search.

I opened this meanwhile - https://github.com/allegroai/clearml-server/issues/138

Generally, it would also be good if the pop-up presented some hints about what went wrong with fetching the experiments. Here, I know the pattern is incomplete and invalid. A less advanced user might not understand what's up.

Not sure if @<1523701087100473344:profile|SuccessfulKoala55> or @<1523701827080556544:profile|JuicyFox94> maybe knows?

I'm trying to decide if ClearML is a good use case for my team 🙂
Right now we're not looking for a complete overhaul into new tools, just some enhancements (specifically, model repository, data versioning).

We've been burnt by DVC and the likes before, so I'm trying to minimize the pain for my team before we set out to explore ClearML.

Hm, that seems less than ideal. I was hoping I could pass some CSV locations. I'll try and find a workaround for that. Thanks!

Okay trying again without detached

See e None @<1523701087100473344:profile|SuccessfulKoala55>

Now my extra_vm_bash_script looks like so:
` deactivate
apt-get install -y gfortran libopenblas-dev liblapack-dev libpq-dev python-is-python3 python3-pip python3-dev proj-bin libgraphviz-dev graphviz graphviz-dev libgdal-dev
apt-get install software-properties-common -y
add-apt-repository ppa:deadsnakes/ppa -y
apt update
apt install python3.7 python3.8 python3.9 python3.7-distutils python3.8-distutils python3.9-distutils python3.10-distutils python3.7-dev python3.8-dev python3.9-dev pyt...

I'll try a hacky-way around it with sed -i 's/include-system-site-packages = false/include-system-site-packages = true/g' clearml_agent_venv/pyvenv.cfg and report back.

But to be fair, I've also tried with python3.X -m pip install poetry etc. I get the same error.

Sorry, not necessarily RBAC (although that is tempting 😉 ), but for now was just wondering if an average joe user has access to see the list of "registered users"?

Worked like a charm

That's fine for the current use-case I believe.
Once the team is happy with the logging functionality, we'll move on to remote execution and things will update.

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)

I guess the thing that's missing from offline execution is being able to load an offline task without uploading it to the backend.
Or is that functionality provided by setting offline mode and then importing an offline task?

Let me double check, one moment

Nope, no other config files

Ah, uhhhh whatever is in the helm/glue charts. I think it’s the allegroai/clearml-agent-k8s-base , but since I hadn’t gotten a chance to try it out, it’s hard to say with certainty which would be the best for us 😛

I'll give it a shot. Honestly, the SDK documentation for both InputModel and OutputModel is (sorry) horrible ...

Can't wait for the documentation revamping.