code: def __post_init__(self):
      self.prompt_column = (
          tuple(
              self.prompt_column,
          )
          if isinstance(self.prompt_column, str)
          else tuple(self.prompt_column)
      )
      super().__post_init__()
  
      self._visibility["limit_chained_samples"] = -1
      self._visibility["mask_prompt_labels"] = -1
  
imports: import os
  from dataclasses import dataclass, field
  from typing import Any, Dict, List
  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.models import text_sequence_to_sequence_modeling_model
  from llm_studio.src.utils.modeling_utils import generate_experiment_name
label_desc: Use image node_id 1 for calling the ConfigNLPSeq2SeqDataset obj's underlying member method code with example usage: obj.__post_init__() without return types