code: def prepare_columns(self, train_df, valid_df):
      train_df.loc[:, "autotrain_text"] = train_df[self.text_column]
      train_df.loc[:, "autotrain_label"] = train_df[self.label_column]
      valid_df.loc[:, "autotrain_text"] = valid_df[self.text_column]
      valid_df.loc[:, "autotrain_label"] = valid_df[self.label_column]
  
      # drop text_column and label_column
      train_df = train_df.drop(
          columns=[self.text_column, self.label_column]
      )
      valid_df = valid_df.drop(
          columns=[self.text_column, self.label_column]
      )
      return train_df, valid_df
  
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 3 for calling the Seq2SeqPreprocessor obj's underlying member method code with example usage: obj.prepare_columns(train_df, valid_df) and returns: train_df,  valid_df