code: def formatting_func_rm(sample: Dict[str, Any]):
      # The FeedbackDataset isn't really set up for RM, 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"], sample["text"][:5]
          elif labels[0] == "c":
              return [
                  (sample["text"], sample["text"][5:10]),
                  (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 4 for calling a global function with example usage: formatting_func_rm(sample) and returns: None, sample,  sample, list