class_docstr: A wrapper class for testing PPOTrainer
class_docstr_tok: ["A","wrapper","class","for","testing","PPOTrainer"]
code: def test_drop_last_dataloader(self):
      self.ppo_config = PPOConfig(
          batch_size=3, mini_batch_size=1, log_with=None
      )
  
      dummy_dataset = self._init_dummy_dataset()
  
      ppo_trainer = PPOTrainer(
          config=self.ppo_config,
          model=self.gpt2_model,
          ref_model=self.gpt2_model_ref,
          tokenizer=self.gpt2_tokenizer,
          dataset=dummy_dataset,
      )
      dummy_dataloader = ppo_trainer.dataloader
  
      self.assertEqual(len(dummy_dataloader), 0)
  
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 6 for calling the PPOTrainerTester obj's underlying member method code with example usage: obj.test_drop_last_dataloader() without return types