Hi ImmensePenguin78 , can you ping the server?
The training pipeline that is considered “best of breed” is committed to Git and deployed by CI/CD; tagged in ClearML clearly.
tagged in ClearML clearly -> this means you have a task in the UI ready for use after this step?
Hi PunyBee36 , what about the pulling of the task? works?
About the running task, I can read in the logs that a new instance was created (i-02fc8...), can you check if you have a running clearml agent on it? if so, the agent will pull the task from the queue, if not, can you check in this instance logs for errors and share?
Hi CheekyToad28 ,
None of the options https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server#deployment works for you?
Hi JitteryCoyote63 ,
Sure you can, you have many https://allegro.ai/docs/use_cases/trains_agent_use_case_examples/ , just pick to one you need 🙂
what do you have under installed packages for this task?
Hi WackyRabbit7 ,
Did you try using  sdk.development.detect_with_pip_freeze  as  true  in your  ~/clearml.conf  file? It should take the same environment as the one you are running from.
You can send  "yet_another_property_name": 1  too, or you can do"another_property_name": {"description": "This is another user property", "value": "1", "type": "int"}
Hi VictoriousPenguin97
sdk.storage.direct_access  is part of the extended support in the paid version.
But I think its not required since ClearML will simply try to access the path directly as it is, and you don’t need to configure it.
👍
Have a great weekend 🙂
The non-pip freeze will have the package your are using in your script, and not the whole env, according to imports and usage
Hi  ConvolutedChicken69 , the  Dataset.upload()  will upload the data as an artifact to the task and will allow others to use the dataset (ClearML agents for example, running and using the data with  Dataset.get()  ).
You are definitely right! We will fix this issue, Thanks 🙂
PanickyMoth78  can I verify the setup with you?
python 3.8?
nvidia/cuda:11.2.2-runtime-ubuntu20.04 as image?
Hi FlatStarfish45 ,
The HPO task will control the HPO process, means it will clone the base task (the one we are optimizing), change the parameters, enqueue it and collect the results.
The base task is the task we want to optimize.
Each one of those two tasks, have different requirements.
You can look at the  https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt#set-up-the-arguments  for how set the base task in the HPO task.
can this be ...
WonderfulArcticwolf3 and CloudySwallow27 are you running it as a service or via the apps? whats the clearml version (not agent)?
Hi JitteryCoyote63 , what commit and branch do you see in the UI?
Hi DisturbedWalrus17 ,
Do you want to clear the parameters from a cloned task?
Hi ColorfulRaven45 , I’ll ask someone from the ClearML Sales team to contact you (can you send me you email in DM?)
Can you share the exception for  --gpus "0,1"   ?
Hi RattySeagull0 ,
Can you try quote the gpus numbers? like  --gpus "0,1"  ?
looks the same issue as  https://github.com/allegroai/trains-agent/issues/35
Hi PanickyFish98 ,
Yes, in order to use  disable_clone_task  flag the base task must be in draft-mode ( created  ).
Great 🙂
If you do wanna change the commit/branch/tag, you can change it from the  data.script  section in the cloned_task object
You have all the other packages in this section except  pyfunctional ?
which ClearML agent version are you running?
Hi SucculentBeetle7 ,
get_local_copy()  will return the entire dataset (the zip file), but you can divide the dataset and have the same parent for all of them, what do you think?
