@<1626028578648887296:profile|FreshFly37> how are you running this locally in the first place?
If you are running pipeline.py with cwd as ev_xx_detection/clearml , then I would not expect you to be able to do from ev_xx_detection.clearml import constants (for example), but import constants directly would work (as constants.py is in the same directory as pipeline.py ). The reason your remote run doesn't work is basically because of this:
cwd is ev_xx_detection/clearml and ev_xx_detection.clearml.constants is imported, but the module that should be imported is actually constants

@<1523701435869433856:profile|SmugDolphin23> I have tried the same method as suggested by you and the pipeline still failed, as it couldn't find "modules". Could you please help me here?

I would like to describe the process again, which I was following:

• I created a queue and assigned 2 workers to the queue.
• In the pipeline.py file, to start the pipeline I used pipe.start(queue="queue_remote") and for the tasks I used pipe.set_default_execution_queue('queue_remote')
• In the working_dir = ev_xxxx_xxtion/clearml I executed the code using python3 pipeline.py
• The pipeline was initiated on queue " queue_remote " on worker 01 & the next tasks were initiated on queue " queue_remote " on worker 02 and it failed, as it couldn't find the modules in worker 02.

Regarding pending pipelines: please make sure a free agent is bound to the queue you wish to run the pipeline in. You can check queue information by accessing the INFO section of the controller (as in the first screenshort)
then by pressing on the queue, you should see the worker status. There should be at least one worker that has a blank "CURRENTLY EXECUTING" entry

@<1523701435869433856:profile|SmugDolphin23> I have tried another way by including pipeline.py in the root directory of the code and executed “python3 pipeline.py” & still faced same issue

It prints "True"

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>

Thank you @<1523701435869433856:profile|SmugDolphin23> It is working now after the addition of repo details into each task. It seems that we need to specify repo details in each task to pull the code & execute the tasks on the worker.

@<1523701435869433856:profile|SmugDolphin23> I used clearml==1.13.2 and now I am upgrading to clearml=1.14.1 version.Also I would give extra information about Clearml-server docker-compose file images versions is latest right now.

@<1523701435869433856:profile|SmugDolphin23> Sure, Thank you for the suggestion. I'll try to add imports as mentioned by you and execute the pipeline & check the functionality.

In Local I'm running using python3 pipelin.py and used pipe.start_locally(run_pipeline_steps_locally=True) in the pipeline to initialize & it's working fine.

what do you get when you run this code?

from clearml.backend_api import Session
print(Session.check_min_api_server_version("2.17"))

@<1523701435869433856:profile|SmugDolphin23> I have attached two screenshots, One is pipeline initialization & other one is the task of the pipeline.

The project's directory is as follows:
The pipeline.py includes the code to run the pipeline & tasks of the pipeline.

├── Makefile
├── README.md
├── ev_xxxxxx_detection
│   ├── __init__.py
│   ├── __pycache__
│   │   └── __init__.cpython-311.pyc
│   ├── clearml
│   │   ├── __pycache__
│   │   ├── clearml_wrapper.py
│   │   ├── constants.py
│   │   ├── data_loader.py
│   │   ├── ev_trainer.py
│   │   ├── pipeline.py
│   │   └── util.py
├── poetry.lock
├── pyproject.toml

@<1523701435869433856:profile|SmugDolphin23> I run the code in order to step1, step2 and step3. And then I run the "pipeline_from_task.py" scripts. I follow the ClearML documentation so whole of the codes taken from github repo.

@<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 :(

@<1523701435869433856:profile|SmugDolphin23> , I’ve updated both the ClearML server and client to the latest version, 1.14.0, as per our previous conversation. However, I’m still encountering the same issue as described earlier.
WebApp: 1.14.0-431
Server: 1.14.0-431
API: 2.28

I attempted to use the same queue for both the controller and the steps, and assigned two workers to this queue. Upon executing the code, the pipeline was initiated on the “queue_remote” queue, and the tasks of the pipeline were also initiated on another worker in the “queue_remote” queue. However, the dataset creation failed because it was unable to locate the Python modules from the current directory as shown in the below screenshot.

Note: I stored the code and its dependencies in a GitHub repository when I executed the pipeline.

Please refer to the attached error screenshot and the code I used to run the pipeline for more details

I also encountered a similar problem. When I run pipeline code I could not see in the deployed pipeline in the ClearML UI and the pipeline's first step does not start in the remote agent machine. It is queued with pending status.

I just use "pip install clearml" command for sdk.

It prints "1.13.3rc0"

Oh I see. I think there is a mismatch between some clearml versions on your machine? How did you run these scripts exactly? (like the CLI, for example python test.py ?)

Or if you ran it via an IDE, what is the interpreter path?

@<1523701435869433856:profile|SmugDolphin23> Can you please help me out here

I have attached the screenshot of logs earlier

what about import clearml; print(clearml.__version__)

Can you please screenshot the INFO tab on the pipeline controller task?

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-repo, we force local script storage (repo="" or repo=False) """

@<1626028578648887296:profile|FreshFly37> I see that create_dataset doesn't have a repo set. Can you try setting it manually via the repo repo_branch repo_commit arguments in the add_function_step method?

how did you install clearml?

how about this one?

import clearml
import os
print("\n".join(open(os.path.join(clearml.__path__[0], "automation/controller.py")).read().split("\n")[310:320]))

@<1657556312684236800:profile|ManiacalSeaturtle63> can you share how you are creating your pipeline?