code: def __post_init__(self):
      if self.text_column is None:
          raise ValueError("text_column must be provided")
  
      # check if text_column and rejected_text_column are in train_data
      if (
          self.prompt_column is not None
          and self.prompt_column not in self.train_data.columns
      ):
          self.prompt_column = None
      if (
          self.rejected_text_column is not None
          and self.rejected_text_column not in self.train_data.columns
      ):
          self.rejected_text_column = None
  
      # make sure no reserved columns are in train_data or valid_data
      for column in RESERVED_COLUMNS + LLM_RESERVED_COLUMNS:
          if column in self.train_data.columns:
              raise ValueError(f"{column} is a reserved column name")
          if self.valid_data is not None:
              if column in self.valid_data.columns:
                  raise ValueError(
                      f"{column} is a reserved column name"
                  )
  
imports: from dataclasses import dataclass
  from typing import Optional
  import pandas
  from datasets import ClassLabel, Dataset, DatasetDict
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 1 for calling the LLMPreprocessor obj's underlying member method code with example usage: obj.__post_init__() without return types