code: def test_batch_size(self):
      # 1 per batch
      aug = nas.ContextualWordEmbsForSentenceAug(
          model_path="distilgpt2", batch_size=1
      )
      aug_data = aug.augment(self.texts)
      self.assertEqual(len(aug_data), len(self.texts))
  
      # batch size = input size
      aug = nas.ContextualWordEmbsForSentenceAug(
          model_path="distilgpt2", 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.ContextualWordEmbsForSentenceAug(
          model_path="distilgpt2", batch_size=len(self.texts) + 1
      )
      aug_data = aug.augment(self.texts)
      self.assertEqual(len(aug_data), len(self.texts))
  
file_path: nlpaug/test/augmenter/sentence/test_context_word_embs_sentence.py
imports: import unittest
  import os
  import torch
  from dotenv import load_dotenv
  import nlpaug.augmenter.sentence
label_desc: Use image node_id 2 for calling the TestContextualWordEmbsAug obj's underlying member method code with example usage: obj.test_batch_size() without return types