class_docstr: `Amazon <https://cs.stanford.edu/people/jure/pubs/reviews-recsys13.pdf>`_ is a Product Review Sentiment Classification dataset.
  
  we use dataset provided by `LOTClass <https://github.com/yumeng5/LOTClass>`_
  
  Examples: # TODO implement this
code: def get_examples(self, data_dir, split):
      examples = []
      label_file = open(
          os.path.join(data_dir, "{}_labels.txt".format(split)), "r"
      )
      labels = [int(x.strip()) for x in label_file.readlines()]
      with open(
          os.path.join(data_dir, "{}.txt".format(split)), "r"
      ) as fin:
          for idx, line in enumerate(fin):
              text_a = line.strip()
              example = InputExample(
                  guid=str(idx), text_a=text_a, label=int(labels[idx])
              )
              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 AmazonProcessor obj's underlying member method code with example usage: obj.get_examples(data_dir, split) and returns: examples