class_docstr: A wrapper class for testing PPOTrainer
class_docstr_tok: ["A","wrapper","class","for","testing","PPOTrainer"]
docstr: Test PPO step with a reference model and custom layers
  The trainer should raise a warning if the argument `num_shared_layers` is set
  together with a reference model.
code: def test_ppo_step_with_ref_and_custom_layers_warning(self):
      """
      Test PPO step with a reference model and custom layers
      The trainer should raise a warning if the argument `num_shared_layers` is set
      together with a reference model.
      """
      # initialize dataset
      dummy_dataset = self._init_dummy_dataset()
  
      num_shared_layers = 6
  
      with self.assertWarns(UserWarning):
          _ = PPOTrainer(
              config=self.ppo_config,
              model=self.gpt2_model,
              ref_model=self.gpt2_model_ref,
              tokenizer=self.gpt2_tokenizer,
              dataset=dummy_dataset,
              num_shared_layers=num_shared_layers,
          )
  
imports: import copy
  import fnmatch
  import gc
  import re
  import tempfile
  import unittest
  import pytest
  import torch
  from huggingface_hub import HfApi, HfFolder, delete_repo
  from parameterized import parameterized
  from pytest import mark
  from requests.exceptions import HTTPError
  from transformers import AutoTokenizer
  from trl import AutoModelForCausalLMWithValueHead, AutoModelForSeq2SeqLMWithValueHead, PPOConfig, PPOTrainer, set_seed
  from trl.core import respond_to_batch
  from .testing_constants import CI_HUB_ENDPOINT, CI_HUB_USER, CI_HUB_USER_TOKEN
  from .testing_utils import require_peft, require_torch_multi_gpu
label_desc: Use image node_id 13 for calling the PPOTrainerTester obj's underlying member method code with example usage: obj.test_ppo_step_with_ref_and_custom_layers_warning() without return types