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25 × Eureka!before exposing our IP to the world, I suggest going over security advisory in the docs: None
as a general note, do not expose your server, the open source version is not designed for it, just put it inside your VPN and it will be fine
Specifically for this one, this is the auto generated docstring from the actual code, so PR to the
https://github.com/allegroai/clearml/blob/e53a76b713910adaf87578c69e86f8154d4ab4c1/clearml/logger.py#L152
metric=image is the name in the dropdown of the denugimages
Hi TrickyRaccoon92
Are you sure plotly (the front-end module displaying the plots in the UI) supports it ?
I'll make sure we fix the example, because as you pointed, it is broken :(
Hi DepressedChimpanzee34
Why do you need to have the configuration added manually ? isn't the cleaml.conf easier ? If not I think OS environments are easier no? I run run above code, everything worked with no exception/warning... What is the try/except solves exactly ?
Are they expanded in the "api_server" ? (I verified on a linux machine, same error, the env in the api_server is not being resolved)
DefiantHippopotamus88 you can create a custom endpoint and do that, but it will be running I the same instance , is this what you are after? Notice that Triton actually supports it already, you can check the pytorch example
Hi IntriguedRat44
Sorry, I missed this message...
I'm assuming you are running in manual mode (i.e. not through the agent), in that case we do not change the CUDA_VISIBLE_DEVICES.
What do you see in the resource monitoring? Is it a single GPU or multiple GPUs?
(Check the :monitor:gpu in the Scalar tab under results,)
Also what's the Trains/ClearML version you are suing and the OS ?
Hi @<1658281099807166464:profile|SmallCamel52>
Lack of authentication in all versions of the fileserver component
Are you leaving the fileserver open to the world ?
Hi ProudMosquito87
My apologies there is still no concrete ETA ...
That said I think a good toy example would really help accelerate this process.
How about opening a PR with a nice hydra example, then we can start discussing implementation details based on the toy example ?
GreasyLeopard35
I can update that the fix to UniformIntegerParameterRange should be pushed with tomorrows release 🙂
(which would fix in turn LogUniformParameterRange)
But every agent is a different pod so I do not know how properly share the folder with images.
Can I conclude Kubernetes running the agents ?
Hmm StrangePelican34
Can you verify you call Task.init before TB is created ? (basically at the start of everything)
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 ?
Hi @<1529271085315395584:profile|AmusedCat74>
ClearML Scheduler where it doesn't reuse the task
What do you mean by doesn't reuse the Task, do you mean you want each time the scheduler is launched to basically overwrite the previous run ?
Hi FrothyShark37
is the task scheduler only acessible through the SDK?
yes, in the open source version this is strictly code based. I know the enterprise tier has a UI for it, but in terms of features I believe this is equivalent
That is awesome!
If you feel like writing a bit about the use-case and how you solved it, I think AnxiousSeal95 will be more than happy to publish something like that 🙂
The problem is of course filling in all the configuration details, so that they are viewable.
Other than that, check out:
https://allegro.ai/docs/task.html#trains.task.Task.export_task
https://allegro.ai/docs/task.html#trains.task.Task.import_task
Sounds good ?
CheerfulGorilla72 could it be the server address has changed when migrating ?
Hmm that makes sense to me, any chance you can open a github issue so we do not forget ? (I do not think it should be very complicated to fix)
Does a pipeline step behave differently?
Are you disabling it in the pipeline step ?
(disabling it for the pipeline Task has no effect on the pipeline steps themselves)
Yes, experiments are standalone as they do not have to have any connecting thread.
When would you say a new "run" vs a new "experiment" ? when you change a parameter ? change data ? change code ?
If you want to "bucket them" use projects 🙂 it is probably the easiest now that we have support for nested projects.
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 ?