@<1691620877822595072:profile|FlutteringMouse14> , what version of the agent are you using?
I think because they create a folder in /opt/clearml/data/mongo_4 and the folder needs same permissions as were made in the setup
From the looks of this example this should be connected automatically actually
https://github.com/allegroai/clearml/blob/master/examples/frameworks/hydra/hydra_example.py
FreshKangaroo33 , what do you mean by syntax examples?
I think this should give you some context on usage 🙂
https://github.com/allegroai/clearml/blob/master/examples/reporting/hyper_parameters.py
Hi @<1523701842515595264:profile|PleasantOwl46> , I'm afraid that such a capability doesn't really exist in ClearML. You could technically populate an experiment using the API.
I'm however curious - what is your use case for this?
Hi @<1821355631278297088:profile|ThoughtlessTiger0> , can you please elaborate a bit on what exactly is the process? Why are steps failing? Is this to be expected?
Check the pre_execute_callback and post_execute_callback arguments of the component.
AbruptWorm50 , can you try deleting your cookies/data on your browser to see if you manage to load the debug samples? I think this might be related: https://github.com/allegroai/clearml/issues/637
GrievingTurkey78 , it appears to be bad methodology on my side as disconnecting the framework won't log any scalars etc...
I think a better solution would be to set the log level to something else, however you will not see 'INFO' messages from the module.
Try something like this:logging.getLogger('clearml.model').setLevel(logging.WARNING)
This will only show you the warnings regarding the models module.
Hi @<1523708920831414272:profile|SuperficialDolphin93> , simply set output_uri=/mnt/nfs/shared in Task.init
I think you can set this code wise as well - https://clear.ml/docs/latest/docs/references/sdk/task#taskforce_requirements_env_freeze
Hi @<1533619716533260288:profile|SmallPigeon24> , I think the worker id is dependent on the worker name, so you can control it this way
I don't think this the intended behavior. Can you please elaborate how it happens exactly?
I am not very familiar with KubeFlow but as far as I know it is mainly for orchestration whereas ClearML offers a full E2E solution 🙂
o, if I pull this file from s3 bucket, I can conclude which chunk I should download to get a specific file. Am I wrong?
I think you're right. Although I'm not sure if you can decompress individual chunks - worth giving it a try!
I also though clearML writes this mapping (
state.json
) into one of its databases: Mongo, Redis, Elasticsearch.
I think the state.json is saved like an artifact so the contents aren't really exposed into one of the dbs
What is the dataset URL you see in the UI? If you go to the dataset, there should be a view to the dataset link
Which version of clearml are you using?
Hi @<1635088270469632000:profile|LividReindeer58> , I think the best ways are either using tags or metadata on the model itself. What do you think?
You need to follow the instructions here - None
Just to make sure we're on the same page, you're referring the machine statistics or ALL scalars don't show up?
Do you see any errors in the apiserver on startup or after?
What exactly would you like to change?
And additionally does the
When executing a Task (experiment) remotely, this method has no effect).
part means that if it is executed in a remote worker inside a pipeline without the dataset downloaded the method will have no effect ?
I think this means the add tags specifically will have no effect
Hi @<1673501397007470592:profile|RelievedDuck3> , no 🙂
Hi @<1578555761724755968:profile|GrievingKoala83> , what happens if you rerun this via the webUI ?
Well if you save it as an artifact, that artifact is accessible by other tasks and passable via the pipeline with monitor_artifacts parameter in add_step()
https://clear.ml/docs/latest/docs/references/sdk/automation_controller_pipelinecontroller#add_step
Hi TrickyFox41 , I'm sorry for the confusion. It appears that the issue is solved in the unreleased version 1.9.2 of the server that should be coming out in the next few days (Thursday or start of next week).
Hi @<1806135344731525120:profile|GrumpyDog7> , what about the load on the server itself? Also, are you downloading from the files server or from some arbitrary source?