I have to admit, I haven't had the time 😞
Trying to get pip to be twice as fast 🤞
https://github.com/pypa/pip/pull/8215
Please keep pinging me, I would really like to follow on it.

Could be nice to write some automation

https://stackoverflow.com/questions/67419800/error-cannot-schedule-new-futures-after-interpreter-shutdown-with-boto3-while

:param list(str) xlabels: Labels per entry in each bucket in the histogram (vector), creating a set of labels for each histogram bar on the x-axis. (Optional)

ThickDove42 you need the latest cleaml-agent RC for the docker setup script (next version due next week)
pip install clearml-agent==0.17.3rc0

Hmm can you test with the latest RC?
pip install clearml==0.17.6rc1

And the correct region ?

Hi @<1734020162731905024:profile|RattyBluewhale45>
What's the clearml agent version? And could you verify with the latest RC?
Lastly how are you running the agent, docker mode? What's the bade container?

Hi FloppyDeer99
Since this thread is a bit old, I might have missed something 🙂
Are we saying the links are not working in the UI ?
(notice the links themselves are generated by the clearml package, so if there was a bug, still not sure here, then old links will remain invalid until manually fixed) Can you verify that the latest clearml generates working links?

JitteryCoyote63 could you send the log maybe ?

you mean The Task already exists or you want to create a Task from the code ?

(BTW: any reason not to use the agent?)

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

GiganticTurtle0 is there any git redundancy on your network ? maybe you could configure a fallback server ?

Hi ReassuredTiger98

but I would rather just define a function that returns the task directly

🙂
Check it out:
https://github.com/allegroai/clearml/blob/36ee3d61209e413a917d8a718fb25f389143cfa1/clearml/automation/controller.py#L205
:param base_task_factory: Optional, instead of providing a pre-existing Task, provide a Callable function to create the Task (returns Task object)

I specifically set is as empty with 

export_data['script']['requirements'] = {}

 in order not to reduce overhead during launch. I have everything installed inside the container

Do you have everything inside the container Inside a venv ?

correct

was consistent, whereas for some reason this old virtualenv decided to use python2.7 otherwise 

Yes,
This sounds like a virtualenv bug I think it will not hurt to do both (obviously we have the information)

Thank you!!! 😍

LOL I keep typing clara without noticing (maybe it's the nvidia thing I keep thinking about)
Carla makes much more sense 😄

Runtime, every time the add_step needs to create a New Task to be enqueued

the second seems like a botocore issue :
https://github.com/boto/botocore/issues/2187

GreasyLeopard35 from the implementation:
https://github.com/allegroai/clearml/blob/fcad50b6266f445424a1f1fb361f5a4bc5c7f6a3/clearml/automation/parameters.py#L215
Which basically returns the "self.base" (default) 10 to the power of the selected value:
10**-3 = 0.001
So how would I get a negative value ?

but then the error occurs, after the training und the validating where succesfuly completed

It seems it is failing on the last eval ? could it be testing is missing? is it the same dataset ? can you verify the file is there? (notice I see a mix of / and \ in the file name, this is odd Windows is \ and linux/mac are / , you should never have a mix)

I think CostlyOstrich36 managed to reproduce?!

@<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.

FierceRabbit20 it seems the Pipeline Task that was created is missing the "installed requirements" section. How are you creating the actual pipeline Task? is this from code?

Hi @<1523701168822292480:profile|ExuberantBat52>
What do you mean by:

• dataset_1 -> script_2 -> dataset_2a dataset creates a script ?

To automate the process, we could use a pipeline, but first we need to understand the manual workflow

Are you sure you added the pytorch channel in clearml.conf ?
https://github.com/allegroai/clearml-agent/blob/822984301889327ae1a703ffdc56470ad006a951/docs/clearml.conf#L64

adding the functionality to clearml-task sounds very attractive!

Hmm, what do you think?
parser.add_argument('--configuration', type=str, default=None, help='Specify local configuration file' ) parser.add_argument('--configuration-name', type=str, default=None, help='configuration section name' ) ... with open(args.configuration, 'rt') as f: create_populate.task.set_configuration_object(args.name, config_text=f.read())Add h...