Hi @<1594863230964994048:profile|DangerousBee35> , can you try with the latest clearml version? can you share initialize_clearml_task function?
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 ClearML task.
tags : list[str]
List of tags to be assigned to the task.
Returns
-------
tuple[Task, Logger]
A tuple containing the ClearML task, and the logger.
"""
task = Task.current_task()
if task is None:
task = CADLUtils.init_clearml_task(
project_name=project_name,
task_name=task_name,
task_type=task_type,
tags=tags
)
logger = task.get_logger()
return task, logger
class CADLUtils:
@staticmethod
def init_clearml_task(project_name: str, task_name: str, task_type: str, tags: list[str] | None = None) -> Task:
"""
Initializes a ClearML task for the current project.
Parameters:
-----------
project_name : str
The name of the project. for nested projects, use the format 'parent_project/child_project'.
task_name : str
The name of the task.
task_type : str
The type of the task. choose from clearml.Task.TaskTypes.
Returns:
--------
Task
The initialized ClearML task.
Example:
--------
task = CADLUtils.init_clearml_task(project_name='my_project', task_name='my_task', task_type='training')
"""
task = Task.init(
project_name=project_name,
task_name=task_name,
task_type=task_type,
tags=tags,
auto_connect_frameworks={"pytorch": False},
reuse_last_task_id=False,
# output_uri="
",
)
return task
will try with the newest version as well