New RunLLM response generated: >>>*# Question* Hello. When running a training job using the kubeflow training operator, I couldn't find a way to make sure worker-0 is always the one that has the global rank 0. Then it becomes a guessing game to find out which one of the pods is the one that has the global rank 0 (which usually has more logging in most training frameworks). Has anyone had a similar issue? # Answer Yes, you can control which worker returns its value by raising an

IgnoreOutputs

exception for all other ranks except rank 0. This ensures that only the worker with rank 0 returns its value to subsequent tasks in the workflow.

import os
from flytekit import task, IgnoreOutputs

@task
def some_task():
    if os.environ.get("RANK") != "0":
        raise IgnoreOutputs()
    # Your code here

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