code: def __post_init__(self):
      super().__post_init__()
      self._possible_values[
          "rejected_answer_column"
      ] = possible_values.Columns(
          prefer_with=lambda column: column
          in ("rejected_answer", "rejected_response")
      )
  
      self._visibility["limit_chained_samples"] = -1
      self._visibility["mask_prompt_labels"] = -1
      self._order.insert(
          "rejected_answer_column", after="answer_column"
      )
  
imports: import os
  from dataclasses import dataclass, field
  from typing import Any
  import llm_studio.src.datasets.text_dpo_modeling_ds
  from llm_studio.python_configs.base import DefaultConfigProblemBase
  from llm_studio.python_configs.text_causal_language_modeling_config import ConfigNLPAugmentation, ConfigNLPCausalLMArchitecture, ConfigNLPCausalLMDataset, ConfigNLPCausalLMEnvironment, ConfigNLPCausalLMLogging, ConfigNLPCausalLMPrediction, ConfigNLPCausalLMTokenizer, ConfigNLPCausalLMTraining
  from llm_studio.src import possible_values
  from llm_studio.src.losses import text_dpo_modeling_losses
  from llm_studio.src.models import text_dpo_modeling_model
  from llm_studio.src.nesting import Dependency
  from llm_studio.src.plots import text_dpo_modeling_plots
  from llm_studio.src.utils.modeling_utils import generate_experiment_name
label_desc: Use image node_id 1 for calling the ConfigDPODataset obj's underlying member method code with example usage: obj.__post_init__() without return types