What version of clearml
are you using? Can you try in a clean python virtual env?
Hi WickedCat12 ,
During Task.init()
you can specify auto_connect_frameworks=False
for the framework you're working with. However please note that this will stop auto reporting scalars etc
https://clear.ml/docs/latest/docs/references/sdk/task#taskinit
@<1544853721739956224:profile|QuizzicalFox36> , are you running the steps from the machine who's config you checked?
Doesn't seem to reproduce for me (just ran pipeline and nothing changed about my project)
And are they the same tasks?
Are you using the OS autoscaler or the PRO version?
ResponsiveHedgehong88 hi,
The best indication would be in the 'INFO' section of the experiment. If it was run via CLI it should have N/A in the worker/queue section
Regarding the packages issue:
What python did you run on originally - Because it looks that 1.22.3 is only supported by python 3.8. You can circumvent this entire issue by running in docker mode with a docker that has 3.7 pre-installed
Regarding the data file loading issue - How do you specify the path? Is it relative?
It looks like there might be a firewall or something of the sort, please try the curl command from the machine itself to verify
Hi,
From the looks of it, it always returns a string. What is your use case for this? Do you have some conditionality on the type of variable the parameters are?
Is there a reason it is requiring pytorch? )
The script you provided has only clearml
as a requirement
Hi @<1739818374189289472:profile|SourSpider22> , can you provide a full log of the run?
Can you see if in the APIserver logs something happened during this time? Is the agent still reporting?
Must have missed this:
I have also hit my computer with a shoe.
Might need bigger shoe 😄
I'm guessing you didn't move ES?
Hi RobustFlamingo1 ,
Can you point to where the website suggests that K8S is a requirement?
I use the ClearML-Agent on a local machine without any K8S. It is certainly not a requirement. From what I understand you can run it on K8S as well.
So to answer your question:
You can definitely use ClearML Orchestration (ClearML-Agent) with OR without K8S
I hope this helps 🙂
@<1691620877822595072:profile|FlutteringMouse14> , can you try upgrading to the latest available? 1.8.1rc2
And you're sure that clearml.conf
points to the correct server with the right credentials?
Hi @<1534496192929468416:profile|EagerGiraffe33> , what if you try to put a specific version of pytorch you've tested on your remote environment in the requirements section of the cloned task?
You can add it to your pip configuration so it will always be taken into account
Or should I set agent.google.storage {}?
Did you follow the instructions in the docs?
Hi @<1546303277010784256:profile|LivelyBadger26> , can you provide a snippet that reproduces this?
Can you also add a full log of the run that was showing the git pass in the startup print?
Hi @<1523711002288328704:profile|YummyLion54> , it hasn't been added to the PRO yet 🙂
I would guess sosudo docker logs --follow trains-webserver
Hi @<1523703397830627328:profile|CrookedMonkey33> , not sure I follow. Can you please elaborate more on the specific use case?
Currently you can add plots to the preview section of a dataset
Hi @<1756488209237282816:profile|IdealCamel64> , I think ClearML would be perfect for that. You can also enable users to have their own remote sessions directly to the GPUs (inside a container even). I'd check out ClearML's orchestration layer + remote sessions:
None
None
Regarding what @<1576381444509405184:profile|ManiacalLizard2> said, he's wrong I'm afraid. ClearML can run ...