code: def formatting_func_dpo(sample: Dict[str, Any]):
      # The FeedbackDataset isn't really set up for DPO, so we'll just use an arbitrary example here
      labels = [
          annotation["value"]
          for annotation in sample["question-3"]
          if annotation["status"] == "submitted"
          and annotation["value"] is not None
      ]
      if labels:
          # Three cases for the tests: None, one tuple and yielding multiple tuples
          if labels[0] == "a":
              return None
          elif labels[0] == "b":
              return (
                  sample["text"][::-1],
                  sample["text"],
                  sample["text"][:5],
              )
          elif labels[0] == "c":
              return [
                  (
                      sample["text"],
                      sample["text"][::-1],
                      sample["text"][:5],
                  ),
                  (
                      sample["text"][::-1],
                      sample["text"],
                      sample["text"][:5],
                  ),
              ]
  
imports: import os
  import re
  from collections import Counter
  from typing import TYPE_CHECKING, Any, Callable, Dict, Iterator, List
  import pytest
  from argilla.client.feedback.dataset import FeedbackDataset
  from argilla.client.feedback.schemas.records import FeedbackRecord
  from argilla.client.feedback.training.base import ArgillaTrainer
  from argilla.client.feedback.training.schemas.base import TrainingTask
  from argilla.client.feedback.training.schemas.return_types import DPOReturnTypes, PPOReturnTypes, RMReturnTypes, SFTReturnTypes
  from datasets import Dataset, DatasetDict
  from peft import LoraConfig, TaskType
  from transformers import AutoModelForCausalLM, AutoModelForSequenceClassification, AutoTokenizer
  from trl import AutoModelForCausalLMWithValueHead
  from tests.integration.client.feedback.helpers import formatting_func_dpo, formatting_func_ppo, formatting_func_rm, formatting_func_sft
  from tests.integration.training.helpers import train_with_cleanup
label_desc: Use image node_id 8 for calling a global function with example usage: formatting_func_dpo(sample) and returns: None, sample,  sample,  sample, list