Hi @<1528908687685455872:profile|MassiveBat21>

However

no useful

template

is created for down stream executions - the source code template is all messed up,

Interesting, could you provide the code that is "created", or even better some way to reproduce it ? It sounds like sort of a bug? or maybe a feature support that is missing.

My question is - what is a best practice in this case to be able to run exported scripts (python code not made availa...

UnevenDolphin73 i would use apiclient:
APIClient().projects.edit(project=project_id, system _tags=[])

*I might have a few typos above but that should be the gist

(just using local server not connected to Internet), am I right?

You can if you host your own git server, Or if your code is a single file / jupyter notebook, then the entire code is stored on the Task.
btw: what is the exact setup, how come there is no git repo?

@<1545216077846286336:profile|DistraughtSquirrel81> shoot an email to "support@clear.ml" and provide all the information you can on the "lost account" (i.e. the one you had the data on), this means email account that created it (or your colleagues emails), and any other information that might help to locate it.

Where do you store those ?

For visibility, after close inspection of API calls it turns out there was no work against the saas server, hence no data

BTW: any specific reason for going the RestAPI way and not using the python SDK ?

These instructions should create the exact chart:
None
What am I missing ?

Hi StrangePelican34
What exactly I not working? Are you getting any TB reports?

Regrading the demoapp, this is just a default server that allows you to start play around with ClearML without needing to setup any of your own servers or signup
That said, I would recommend to sign up (totally free) on the community server
https://app.community.clear.ml/

Okay there should not be any difference ... 😞

Hi SteadySeagull18

However, it seems to be entirely hanging here in the "Running" state.

Did you set a an agent to listen to the "services" queue ?
Someone needs to run the pipeline logic itself, it is sometimes part of the clearml-server deployment but not a mist

Hi @<1534706830800850944:profile|ZealousCoyote89>

We'd like to have pipeline A trigger pipeline B

Basically a Pipeline is a Task (of a specific Type), so you can have pipeline A function clone/enqueue the pipelineB Task, and wait until it is done. wdyt?

FloppyDeer99 what am I seeing in the screenshot ?

But why the url in es is different from it in web UI?

They are not really different, but sometimes the "url quote" is an issue (this is the process a browser will take a string url like a/b and convert it to a%2fb ),
I remember that there was an issue involving double quoting (this is when you have: a/b -> a%2fb -> a%252fb ), notice the last one replace "%" with "%25" as in your example...
Let me know i...

SoreDragonfly16 the torchvision warning has nothing to do with the Trains warning.
The Trains warning means that somehow someone changes the state of the Task from running (in_progress) to "stopped" (aborted). Could it be one of the subprocesses raised an exception ?

So we basically have two options, one is when you call Dataset.get_local_copy() , we register it on the Task automatically, the other is a more explicit, with something like:
ds = Datasset.get(...) folder = ds.get_local_copy() task.connect(ds, name=train) ... ds_val = Datasset.get(...) folder = ds_val.get_local_copy() task.connect(ds_val, name=validate)wdyt?

and then?

The thing is programmatically this is not easy to do as API, because at the end the "function" (i.e. LCI) never leaves, it connects to the SSH and stays

But you can query the Task it creates, the project is known, the user is known and it is of special type/tag

Hi @<1546665666675740672:profile|AttractiveFrog67>

• Make sure you stored the model's checkpoint (either pass output_uri=True in Task.init or manually upload)
• When you call Task.init pass " continue_last_task=True "
• Now you can do last_checkpoint=task.models["output"][-1].get_local_copy() and all you need is to load last_checkpoint

JitteryCoyote63 see if upgrading the packages as they suggest somehow fixes it.
I have the feeling this is the same problem (the first error might be trains masking the original error)

the only problem with it is that it will start the task even if the task is completed

What is the criteria ?

it handles 2FA if my repo lies in Github and my account needs 2FA to sign in

It does not 😞

ImmensePenguin78 this is probably for a different python version ...

Here, I

know

the pattern is incomplete and invalid. A less advanced user might not understand what's up.

Basically like your suggestion that if the request fails while typing instead of the error popup the search bar will turn "dark red", and on the next key stroke will be "cleaned" ?

Hi MassiveBat21
CLEARML_AGENT_GIT_USER is actually git personal token
The easiest is to have a read only user/token for all the projects.
Another option is to use the ClearML vault (unfortunately not part of the open source) to automatically take these configuration on a per user basis.
wdyt?

LovelyHamster1 NICE! 👍

Hi IrritableJellyfish76
https://clear.ml/docs/latest/docs/references/sdk/task#taskget_tasks

task_name

(

str

) – The full name or partial name of the Tasks to match within the specified

project_name

(or all projects if

project_name

is

None

). This method supports regular expressions for name matching. (Optional)

You are right, this is a bit confusing, I will make sure that we add in the docstring an examp...

The additional edges in the graph suggest that these steps somehow contain dependencies that I do not wish them to have.

PanickyMoth78 I think I understand what you are saying, but it is hard to see if there is a "bug" here or a feature...
Can you post the full code of the pipline?

JitteryCoyote63 I think that without specifically adding torch to the requirements, the agent will not be able to automatically resolve the correct cuda/torch version. Basically you should add torch to the requirements.txt file, and provide it to Task create, or use Task.force_requirements_env_freeze

This really makes little sense to me...

Can you send the full clearml-session --verbose console output ?

Something is not working as it should obviously, console output will be a good starting point

Would you have an example of this in your code blogs to demonstrate this utilisation?

Yes! I definitely think this is important, and hopefully we will see something there 🙂 (or at least in the docs)