code: def test_batch_size(self):
      # 1 per batch
      aug = nas.AbstSummAug(model_path="t5-small", batch_size=1)
      aug_data = aug.augment(self.texts)
      self.assertEqual(len(aug_data), len(self.texts))
  
      # batch size = input size
      aug = nas.AbstSummAug(
          model_path="t5-small", batch_size=len(self.texts)
      )
      aug_data = aug.augment(self.texts)
      self.assertEqual(len(aug_data), len(self.texts))
  
      # batch size > input size
      aug = nas.AbstSummAug(
          model_path="t5-small", batch_size=len(self.texts) + 1
      )
      aug_data = aug.augment(self.texts)
      self.assertEqual(len(aug_data), len(self.texts))
  
      # input size > batch size
      aug = nas.AbstSummAug(model_path="t5-small", batch_size=2)
      aug_data = aug.augment(self.texts * 2)
      self.assertEqual(len(aug_data), len(self.texts) * 2)
  
file_path: nlpaug/test/augmenter/sentence/test_abst_summ.py
imports: import unittest
  import os
  import torch
  from dotenv import load_dotenv
  import nlpaug.augmenter.sentence
  import nlpaug.util.text.tokenizer
label_desc: Use image node_id 2 for calling the TestAbstSummAug obj's underlying member method code with example usage: obj.test_batch_size() without return types