code: def df():
      return pd.DataFrame(
          {
              "prompt_column": [f"prompt {i}" for i in range(200)],
              "answer_column": [
                  f"chosen_response {i}" for i in range(200)
              ],
              "rejected_answer_column": [
                  f"rejected_response {i}" for i in range(200)
              ],
          }
      )
  
file_path: h2o-llmstudio/tests/src/datasets/test_text_dpo_modeling_ds.py
imports: import numpy
  import pandas
  import pytest
  import torch
  from tqdm import tqdm
  from llm_studio.python_configs.text_causal_language_modeling_config import ConfigNLPCausalLMTokenizer
  from llm_studio.python_configs.text_dpo_modeling_config import ConfigDPODataset, ConfigProblemBase
  from llm_studio.src.datasets.text_dpo_modeling_ds import CustomDataset
label_desc: Use image node_id 1 for calling a global function with example usage: df() and returns: pd