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Hi Team, I Am Trying To Run A Pipeline Remotely Using Clearml Pipeline And I’M Encountering Some Issues. Could Anyone Please Assist Me In Resolving Them?

Hi Team,

I am trying to run a pipeline remotely using ClearML pipeline and I’m encountering some issues. Could anyone please assist me in resolving them?

Issue 1 : After executing the code, the pipeline is initiated on the “queue_remote_start” queue and the tasks of the pipeline are initiated on the “queue_remote” queue. However, the creation of the dataset failed because it couldn’t find the Python modules from the current directory.

Issue 2 : I also attempted to use the same queue for both pipe.start and pipe.set_default_execution_queue . However, the tasks of the pipeline remained in the pending and queued state and didn’t proceed to the next step.

To run the pipeline remotely, I have created two different queues and assigned a worker to each using the following commands:

clearml-agent daemon --detached --create-queue --queue queue_remote
clearml-agent daemon --detached --create-queue --queue queue_remote_start

I then executed the following command to run the pipeline remotely:

python3 pipeline.py

The code for the Pipeline from Functions is as follows:

# Create the PipelineController object
    pipe = PipelineController(
        name="pipeline",
        project=project_name,
        version="0.0.2",
        add_pipeline_tags=True,
    )

pipe.set_default_execution_queue('queue_remote')

pipe.add_function_step(
    name='step_one',
    function=step_one,
    function_kwargs={
            "train_file": constants.TRAINING_DATASET_PATH,
            "validation_file": constants.VALIDATAION_DATASET_PATH,
            "s3_output_uri": constants.CLEARML_DATASET_OUTPUT_URI,
            "dataset_project": project_name,
            "dataset_name": constants.CLEARML_TASK_NAME,
            "use_dummy_dataset": use_dummy_model_dataset,
        },
        project_name=project_name,
        task_name=create_dataset_task_name,
        task_type=Task.TaskTypes.data_processing,
    )

pipe.start(queue="queue_remote_start")

Could anyone please provide a solution on how to successfully run the pipeline remotely? Any help would be greatly appreciated.

  
  
Posted 9 months ago
Votes Newest

Answers 39


@<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
image

  
  
Posted 9 months ago

Hi!
It is possible to use the same queue for the controller and the steps, but there needs to be at least 2 agents that pull tasks from that queue. Otherwise, if there is only 1 agent, then that agent will be busy running the controller and it won't be able to fetch the steps.

Regarding missing local packages: the step is ran in a temporary directory that is different than the directory the script is originally in. To solve this, you could add all the modules/files you are interested in in a git repository. If you do, that repository will be cloned by the agent when running the steps, which will make the packages accessible.

  
  
Posted 9 months ago

image

  
  
Posted 9 months ago

@<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.
  
  
Posted 9 months ago

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>
image

  
  
Posted 9 months ago

sure, I'll add those details & check. Thank you

  
  
Posted 9 months ago

@<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

image

  
  
Posted 9 months ago

@<1626028578648887296:profile|FreshFly37> can you please screenshot this section of the task? Also, how does your project's directory structure look like?
image

  
  
Posted 9 months ago

ok, that is very useful actually

  
  
Posted 9 months ago
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