Also: what's the purpose of storing the pipeline arguments as artifacts then? When it runs remotely it still runs the main script as entrypoint and not the pipeline function directly, so all the arguments will be replaced by what is passed to the function during the remote execution, right?

Hi @<1570220858075516928:profile|SlipperySheep79> , I think it depends on your code. Can you provide a self contained code snippet that reproduces this?

@<1570220858075516928:profile|SlipperySheep79> depending on a local file is always an issue - would try to connect a configuration based on this file, so that it will be loaded when running locally and than retrieved from the backend when running remotely

Hi @<1523701435869433856:profile|SmugDolphin23> , I just tried it but Task.current_task() returns None even when running in remotely

How about if Task.running_locally(): ?

@<1523701435869433856:profile|SmugDolphin23> then the issue is that config is not set. I also tried with:

import yaml
import argparse
from my_pipeline.pipeline import run_pipeline
from clearml import Task

parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)

if __name__ == '__main__':
    if Task.running_locally()::
      args = parser.parse_args()
      with open(args.config) as f:
          config = yaml.load(f, yaml.FullLoader)
    else:
      config = None
    run_pipeline(config)

But then it prints None , so the pipeline parameters are completly ignored

basically, I think that the pipeline run starts from __ main_ _ and not the pipeline function, which causes the file to be read

I've upladed an example here for simiplicity: None

Hi @<1570220858075516928:profile|SlipperySheep79> ! What happens if you do this:

import yaml
import argparse
from my_pipeline.pipeline import run_pipeline
from clearml import Task

parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)

if __name__ == '__main__':
    if not Task.current_task():
      args = parser.parse_args()
      with open(args.config) as f:
          config = yaml.load(f, yaml.FullLoader)
    run_pipeline(config)

For instance, I have in my_pipeline/__main__.py :

import yaml
import argparse
from my_pipeline.pipeline import run_pipeline

parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True)

if __name__ == '__main__':
    args = parser.parse_args()
    with open(args.config) as f:
        config = yaml.load(f, yaml.FullLoader)
    run_pipeline(config)

and in my_pipeline/pipeline.py :

@PipelineDecorator.pipeline(
    name='Main',
    project=None,
    default_queue='default',
    pipeline_execution_queue='default',
    start_controller_locally=False,
    repo='

',
    add_run_number=False)
def run_pipeline(config: Dict):
    print(config)

I'm running this on an agent in docker mode

Hi @<1523701087100473344:profile|SuccessfulKoala55> , I think the issue is where to put the connect_configuration call. I can't put it inside run_pipeline because it's only running remotely and it doesn't have access to the file, and I can't put it in the script before the call to run_pipeline since the task has not been initialized yet.