code: def test_prepare_batch(self):
      tokenizer = self.tokenizer_class.from_pretrained(
          "microsoft/prophetnet-large-uncased"
      )
  
      src_text = [
          "A long paragraph for summarization.",
          "Another paragraph for summarization.",
      ]
      expected_src_tokens = [
          1037,
          2146,
          20423,
          2005,
          7680,
          7849,
          3989,
          1012,
          102,
      ]
      batch = tokenizer(src_text, padding=True, return_tensors="pt")
      self.assertIsInstance(batch, BatchEncoding)
      result = list(batch.input_ids.numpy()[0])
      self.assertListEqual(expected_src_tokens, result)
  
      self.assertEqual((2, 9), batch.input_ids.shape)
      self.assertEqual((2, 9), batch.attention_mask.shape)
  
imports: import os
  import unittest
  from transformers import BatchEncoding
  from transformers.models.bert.tokenization_bert import BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace
  from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
  from transformers.testing_utils import require_torch, slow
  from ...test_tokenization_common import TokenizerTesterMixin
label_desc: Use image node_id 14 for calling the ProphetNetTokenizationTest obj's underlying member method code with example usage: obj.test_prepare_batch() without return types