code: def __post_init__(self):
      super().__post_init__()
  
      self._visibility["output_directory"] = -1
  
      self._possible_values["llm_backbone"] = possible_values.String(
          values=(
              "t5-small",
              "t5-base",
              "t5-large",
              "google/flan-t5-small",
              "google/flan-t5-base",
              "google/flan-t5-large",
              "google/flan-ul2",
          ),
          allow_custom=True,
      )
  
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 ConfigProblemBase obj's underlying member method code with example usage: obj.__post_init__() without return types