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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 11 months ago
Votes Newest

Answers 39


what about import clearml; print(clearml.__version__)

  
  
Posted 11 months ago

@<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.

  
  
Posted 11 months ago

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

  
  
Posted 11 months ago

what do you get when you run this code?

from clearml.backend_api import Session
print(Session.check_min_api_server_version("2.17"))
  
  
Posted 11 months ago

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.

  
  
Posted 11 months ago

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?

  
  
Posted 11 months ago

image

  
  
Posted 11 months ago

@<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

  
  
Posted 10 months ago

@<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.

  
  
Posted 10 months ago

@<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

  
  
Posted 10 months ago

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.

  
  
Posted 11 months ago

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

  
  
Posted 11 months ago

@<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?

  
  
Posted 10 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 10 months ago

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

  
  
Posted 10 months ago

I ran it via IDE. I am using conda environment and when I list the clearml packages it looks like in the below. The interpreter match with base environment.
image

  
  
Posted 11 months ago

@<1626028578648887296:profile|FreshFly37> can you share also logs of task ? It may give an idea.

  
  
Posted 11 months ago

how did you install clearml?

  
  
Posted 11 months ago

@<1657556312684236800:profile|ManiacalSeaturtle63> what clearml SDK version are you using? I believe there was a bug related to pipelines not showing in the UI, but that was fixed in clearml==1.14.1

  
  
Posted 11 months ago

image

  
  
Posted 11 months ago

I have attached the screenshot of logs earlier

  
  
Posted 10 months ago

For the clearml-server installation I follow the documentation steps one by one. Link is : None

  
  
Posted 11 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 11 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 11 months ago

ok, that is very useful actually

  
  
Posted 11 months ago

It prints "True"

  
  
Posted 11 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 11 months ago

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]))
  
  
Posted 11 months ago

@<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 :(

  
  
Posted 11 months ago

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.

  
  
Posted 10 months ago
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