class_docstr: Yahoo! Answers Topic Classification Dataset
  
  Examples:
  
  ..  code-block:: python
  
      from openprompt.data_utils.text_classification_dataset import PROCESSORS
  
      base_path = "datasets/TextClassification"
code: def get_examples(self, data_dir, split):
      path = os.path.join(data_dir, "{}.csv".format(split))
      examples = []
      with open(path, encoding="utf8") as f:
          reader = csv.reader(f, delimiter=",")
          for idx, row in enumerate(reader):
              label, question_title, question_body, answer = row
              text_a = " ".join(
                  [
                      question_title.replace("\\n", " ").replace(
                          "\\", " "
                      ),
                      question_body.replace("\\n", " ").replace(
                          "\\", " "
                      ),
                  ]
              )
              text_b = answer.replace("\\n", " ").replace("\\", " ")
              example = InputExample(
                  guid=str(idx),
                  text_a=text_a,
                  text_b=text_b,
                  label=int(label) - 1,
              )
              examples.append(example)
      return examples
  
imports: import os
  import json, csv
  from abc import ABC, abstractmethod
  from collections import defaultdict, Counter
  from typing import List, Dict, Callable
  from openprompt.utils.logging import logger
  from openprompt.data_utils.utils import InputExample
  from openprompt.data_utils.data_processor import DataProcessor
label_desc: Use image node_id 2 for calling the YahooProcessor obj's underlying member method code with example usage: obj.get_examples(data_dir, split) and returns: examples