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2 × Eureka!@<1523701435869433856:profile|SmugDolphin23> I retry the same scenario with clearml==1.14.1 package but still it does not show me the pipelines not showing in the UI :(
For the clearml-server installation I follow the documentation steps one by one. Link is : None
When I run it from command line everything return back to normal and pipeline is visible for now. Thank you very much for your helps, time and feedbacks 🙂 @<1523701435869433856:profile|SmugDolphin23>
Hi @<1523701070390366208:profile|CostlyOstrich36> thanks for your response, I just follow documentation with this link None and run codes in this github repository None . In the github repo I run the scripts in order, " [step1_dataset_artifact.py](https://github.com/allegroai/clearml/blob/master/examples/pipeline/step1_datas...
@<1523701435869433856:profile|SmugDolphin23> you are right. When I added more worker to queue and it released from pending status. However when I click the pipelines in the screenshoot, I could not see pipeline schema. It shows me "no pipeline to show" text like in below. Do you have any idea ? I should see each step box when I click the pipeline right ?
 Did you add only storage information under the clearmlConfig parameter in values.yaml file ? @<1661542579272945664:profile|SaltySpider22>
@<1626028578648887296:profile|FreshFly37> can you share also logs of task ? It may give an idea.
There are two task available in the experiments list as you can see in below. I click the step_1 INFO tab and informations like this. There is no available pipeline controller task maybe thats why UI does not show up the pipeline.
This print string like in below. """
if not self._task:
task_name = name or project or '{}'.format(datetime.now())
if self._pipeline_as_sub_project:
parent_project = (project + "/" if project else "") + self._pipeline_section
project_name = "{}/{}".format(parent_project, task_name)
else:
parent_project = None
project_name = project or 'Pipelines'
# if user disabled the auto-...
If you push it to the central registry be sure that agent machine should be able to pull image from central registry.
You can push it to central registry or just load it in the clearml-agent machine. Agent will create a container from this image.
While creating task you can pass docker parameter to specify the image. For example "Task.create(docker=yourcustomimage)"