Hi, sure, there is nothing special there, even some redundancy.

def initialize_clearml_task(
        project_name: str = None,
        task_name: str = None,
        task_type: str = None,
        tags: list[str] = None,
) -> tuple[Task, Logger]:
    """
    Initialize and configure a ClearML task.

    Parameters
    ----------
    project_name : str
        Name of the ClearML project.
    task_name : str
        Name of the ClearML task.
    task_type : str
        Type of the ClearM...

installed packages before the task is running:

# Python 3.10.10 | packaged by Anaconda, Inc. | (main, Mar 21 2023, 18:39:17) [MSC v.1916 64 bit (AMD64)]

GitPython == 3.1.31
bokeh == 2.4.3
boto3 == 1.26.158
botocore == 1.29.158
clearml == 1.11.1
h5py == 3.8.0
holoviews == 1.16.0
joblib == 1.2.0
lightgbm == 3.3.5
mat73 == 0.60
matplotlib == 3.7.1
numpy == 1.23.5
pandas == 1.5.3
pytest == 7.3.1
scikit_learn == 1.3.0
scipy == 1.10.1
shapely == 2.0.1
sktime == 0.21.0
statsmodels == 0.13.5
t...

i don't have one, as i said it is not very reproduceable. the same code runs fine one time, and another time (running the exact same experiment) it works the same but with the logging issues. as i mentioned, IMO it is not something related to the code itself but to connectivity with clearml servers. i'm running on GCP machines, which is not the first time i'm experiencing connectivity issues with clearml when working on them (we migrated from AWS ec2 a few weeks ago). the first issue was with...

from the consule logs i can see that:
entry_point = preprocessing.py
working_dir = Scripts/Volvo/volvo_data_alignment