It seems like you are correct, everything should just work. Are you still getting the error? What's the clearml agent version?

Hi GreasyRaven35
You should set the output_uri, in Task init, it will auto upload the model, and register the remote location URL
task = Task.init(..., output_uri=True)You can also specify a target bucket, if you configured credentials (e.g. output_uri=" s3://bucket ")

Hi ImpressionableRaven99
Yes, it is 🙂
Call this one before task.init, and it will run offline (at the end of the execution, you will get a link to the local zip file of the execution)
Task.set_offline(True)Then later you can import it to the system with:
Task.import_offline_session('./my_task_aaa.zip')

yes

argument saying always create from code

can be helpful

@<1523701523954012160:profile|ShallowCormorant89> any chance you can open a github issue on that, just so we do not forget ?

if we can edit the configuration objects of a pipeline, that can be beneficial too. which we're unable to do from UI

Actually you already can, after you clone the pipeline, you can press on details then go to configuration Tab, and edit the pipeline object. The format is HOCON (...

If I access the dataset on the same location directly it works fine:

wait, I'm confused, how is it the datset us there? did it download the dataset?

are you saying this line for example will fail? (assuming you actually have a dataset by that name)

data_path = Dataset.get(dataset_name="002_Datenset_MASAM_for_fintuning", alias="002_Datenset_MASAM_for_fintuning").get_local_copy()

CLI? Code ?

ClumsyElephant70 yes there is 🙂
clearml-agent build --id <task id> --target <folder>(I might have a typo there, but you can basically check the full help clearml-agent build --help )

JitteryCoyote63 Should be quite safe, there is no major change that I'm aware of on the ClearML side that can effect it.
That said, wait for after the weekend, we are releasing a new ClearML package, I remember there was something with the model logging, it might not directly have something to do with ignite, but worth testing on the latest version.

p.s. StraightCoral86 I might be missing something here, please feel free to describe the entire execution scenario and what you are trying to achieve 🙂

feature value distribution over time

You mean how to create this chart? None

Simple file transfer test gives me approximately 1 GBit/s transfer rate between the server and the agent, which is to be expected from the 1Gbit/s network.

Ohhh I missed that. What is the speed you get for uploading the artifacts to the server? (you can test it with simple toy artifact upload code) ?

Hi MelancholyElk85

Can I manually delete 

.zip

 files with datasets in 

.clearml/cache/storage_manager/datasets

 directory?

Yes, you can. I "think" the .zip is stored for easier access, but you can delete it, as long as the "extracted" folder exists, it should be fine.

his means that you guys internally catch the argparser object somehow right?

Correct 🙂 this is how you get the type checking casting abilities, and a few other perks

It's seems you are are getting 401 unauthorized , is this the same domain? I'm assuming the issue the logged in cookie is not sent?

Hi @<1729309131241689088:profile|MistyFly99>
notice that the files server need to have an "address" that can be accessed from the browser, data is stored in a federated manner. This means your browser is directly accessing the files server, not through the API server, I'm assuming the address is not valid?

Happy to hear 🙂

Wtf? can you try with = (notice single not double)?

channels:
- defaults
- conda-forge
- pytorch
dependencies:
- cudatoolkit=11.1.1
- pytorch=1.8.0

This is only in the preview right ?

quick video of the search not working

Thank you! this is very helpful, passing along to front-end guys 🙂

and ctrl-f (of the browser) doesn’t work as lines below not loaded (even when you scroll it will remove the other lines not visible, so you can’t ctrl-f them)

Yeah, that's because they are added lazily

What's the OS running the server?

😂

I'm trying to create a task that is not in repository root folder.

JuicyFox94 If the Task is not in a repo folder, you mean in a remote repository right ?
This means the repo should be in the form of " https://github.com/ " or "ssh://"
It failed in deducing this is a remote repository (maybe we can improve the auto detection?!)

Sure thing! this feature is all you guys, ask and shall receive 🙂

I was able to successfully enqueue the task but only entrypoint script is visible to it and nothing else.

So you passed a repository link is it did not show on the Task ?
What exactly is missing and how the Task was created ?

The address is valid. If i just go to the files server address on my browser,

@<1729309131241689088:profile|MistyFly99> what is the exact address of those files? (including the http prefix) and what is the address of the web application ?

Okay ConfusedPig65 I found the problem. For some reason the latest TF.keras.load_model . save_model is not tracked.
I'll make sure we push a fix later today

Hi @<1673501379764686848:profile|VirtuousSeaturtle4>

What I dont get is that the example does not refer to a bucket path. What bucket path should I specify ?

you mean to store data?

Great, thanks!

😊

Hi GiddyTurkey39
us the config file connect to the Task via Task.connect_configuration ?

So I have a task that just loads a model, but I don't see it as an artifact in the UI

You should see it under Artifacts, Input model if you are calling Keras load function (or similar)