clearml==1.9.1
clearml-agent==1.5.2

I am not self hosting the server, using the one provided by clearml side

sure, I ll check and update

I see you want to use the services queue for both the pipeline controller and pipeline steps, but you have only one worker/agent listening to this queue. In this case you need at least 2 agents listening to the services queue. Try spawning an additional agent that listens to this queue and let me know how it goes .

It ran, thanks.. but that original problem persisits. Pipeline is running once all the tasks completed.

Can you please attach the code for the pipeline?

What version of clearml , clearml-agent & server are you using?

Hey @<1537605940121964544:profile|EnthusiasticShrimp49> I updated clearml but now the issue is my pipeline is stuck here.
Previously it was working fine till the above mentioned issue and I made no change except the mentioned.

@<1537605940121964544:profile|EnthusiasticShrimp49> is this a code issue or some bug?

one

Hi @<1585078763312386048:profile|ArrogantButterfly10> , does the controller stay indefinitely in the running state?

And how many agents do you have listening on the “services“ queue?

Can you update the clearml version to latest (1.11.1) and see whether the issue is fixed?

from clearml import Task
from clearml.automation import PipelineController
pipe = PipelineController(name='PIPE_TEST_3',project='PIPE_TEST_3',version="0.0.1",add_pipeline_tags=False)

pipe.add_parameter("url",
" None ",
"dataset_url"
)

pipe.set_default_execution_queue('services')

pipe.add_step(name="stage_data",
base_task_project="PIPE_TEST_3",
base_task_name="Pipeline step 1 dataset artifact",
parameter_override={"General/dataset_url": "${pipeline.url}"})

pipe.add_step(
name="stage_process",
parents=["stage_data"],
base_task_project="PIPE_TEST_3",
base_task_name="Pipeline step 2 process dataset",
parameter_override={
"General/dataset_url": "${stage_data.artifacts.dataset.url}",
"General/test_size": 0.25,
}
)

pipe.add_step(
name="stage_train",
parents=["stage_process"],
base_task_project="PIPE_TEST_3",
base_task_name="Pipeline step 3 process dataset",
parameter_override={"General/dataset_task_id": "${stage_process.id}"},

)

# pipe.start_locally()
pipe.start(queue='services')

yes

Ignore default, I am trying to run with another docker, but it is also stuck as same