The problem is resolved by doing a git push. Somehow the git diff didn't capture the difference in requirements.txt in the project. I can't reproduce the same issue after this as well.

I see, so its a path. Another question, as far as i can tell, clearml-data will download entire datasets before starting training. This isn't very ideal when we are dealing with billions of datasets (E.g. WE might want to download a subset at a time, send to GPU for training and then use the CPU to concurrently pull another subset.). Any comments on this?

Ok. I noted this is due to the venv_update setting. It needs to be disabled as it has a dependancy on the internet url. We can close this.

No, i can't see the files. But i can see if i don't use ':port' in the URL when uploading. I can't access the machine today, i'll try to check the S3 logs when i'm back.

Hi, Self-hosted using docker-compose.

Ok thanks, looking forward to it. Would you advise on the bug you encountered?

Hi, this is the setup.

client
from clearml import Task, Logger task = Task.init(project_name='DETECTRON2',task_name='Train',task_type='training') task.set_base_docker("quay.io/fb/detectron2:v3 --env GIT_SSL_NO_VERIFY=true --env TRAINS_AGENT_GIT_USER=testuser --env TRAINS_AGENT_GIT_PASS=testuser" ) task.execute_remotely(queue_name="single_gpu", exit_process=True)
k8s_glue_example.py spawned a pod and starts running.

ClearML UI -> Experiment -> Results -> Console.
` At the top it will pri...

Yeah me 3.

clearml=1.0.3
python=3.8.10
clearml-data upload --id 12314jhg42342j4j --storagehttp://ecs.ai is an on-prem DELL EMC ECS that serves as our S3 storage configured with s self signed cert.

Thanks this would be a good alternative before the enterprise version comes in. How is this different from argparser btw?

Hi, for both of them,  args.lastiter  is the exact same value. But when plotted out, they are 2 actually iterations apart.

yes, previously run experiments. I will just kill clearml-elastic container if that may solve the problem.

I'm not familiar with elastic. What role does elastic play in ClearML?

Okay this part I missed, why would you need to add additional "catalog" when you have the UI?

Yeah this is the part i am trying to reconcile. I don't see any UI for datasets, Or is this a feature of hyperdatasets and i just mixed them up.

Thanks that did solve the problem, the tasks are running again.

Setting the credentials on agent machine means the users cannot use their own credentials since an k8s glue agent serves multiple users.

Referencing your suggestion, we can configure output_uri on task.set_base_docker() but how should we do this for the credentials?

docker exec clearml-elastic curl zsh: no matches found:

I meant the dataset id.

Hi i missed this. Is there a recording?

Hi SuccessfulKoala55 , just wondering how i can follow up on this.

[root@2c7498711bef elasticsearch]# curl -XGET `
yellow open events-training_stats_scalar-d1bd92a3b039400cbafc60a7a5b1e52b 4hAFNtGkRr-CHNGnUYfbTA 1 1 4724 271 660.9kb 660.9kb
yellow open events-log-d1bd92a3b039400cbafc60a7a5b1e52b M3qgFy1HRU2PibDOr1YOdw 1 1 1221 20 1013.6kb 1013.6kb
red open worker_stats_d1bd92a3b039400cbafc60a7a5b1e52b_2021-05 EQK8mnlhRxCrrKK3clcUFA 1 1
red open queue_metrics_d1bd92a3b039400cbafc60a7a5b1e52b_...

i see. Can i take it that when the client uses
task.execute_remotely(queue_name="1gpu", exit_process=True)then none of the content in its clearml.conf will be used, except for the API part. And Clearml simply uses whatever is on the Agent side.
api { # Notice: 'host' is the api server (default port 8008), not the web server. api_server: web_server: files_server: # Credentials are generated using the webapp, `
# Override with os environment: ...

If we run all the rank 0 and rank n tasks individually, it's defeats the purpose of using ClearML.

the hackathon is 3 days.

ok thanks.

alright thanks. Its impt we clarify it works before we migrate the ifra.

Hi erez, i think i would want to reference the code that transformed the data. Take for example, i received 10k images, i performed some transformation and save it as a next version before i split it up for my ML training. Some time later, i receive a new set of 10k images and wants to apply the same transformation and then append it to the previous 10k as another version. Clearml-data does well for the data-versioning part, but in terms of data provenance, its not clear how i can associate t...

Hi, i tried the k8s-glue on my k8s setup and needed some clarifications on some of the arguments.
--queue. Does this only refer to default and service? How can i create new queue to which it can sync with the ClearML server? --ports-mode. I'm not sure what ports mode does. doc says "add a label to the pod which can be used as service". Which pod is it referring to in the first place? All args pertaining to --ports-mode. (E.g. base-pod-num, gateway-address...etc) --overrides-yaml. What is the ...

The doc also mentioned preconfigured services with selectors in the form of
"ai.allegro.agent.serial=pod-<number>" and a targetPort of 10022. Would you have any examples of how to do this?

Hi. The upgrade seems to go well but i'm seeing one wierd output. When i ran a task and observe the software installed under the execution tab , i still see clearml=0.17 . Is this expected?