code: def test_call(self):
      notes = self.get_input_notes()
  
      output = self.tokenizer(
          notes,
          return_tensors="pt",
          padding="max_length",
          truncation=True,
          max_length=10,
          return_attention_mask=True,
      )
  
      # check the output type
      self.assertTrue(isinstance(output, BatchEncoding))
  
      # check the values
      expected_output_token_ids = torch.tensor(
          [
              [134, 133, 74, 135, 77, 132, 77, 133, 77, 82],
              [134, 133, 74, 136, 132, 74, 134, 134, 134, 134],
          ]
      )
      expected_output_attention_mask = torch.tensor(
          [
              [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
              [1, 1, 1, 1, 1, 1, 0, 0, 0, 0],
          ]
      )
  
      self.assertTrue(
          torch.allclose(
              output["token_ids"], expected_output_token_ids, atol=1e-4
          )
      )
      self.assertTrue(
          torch.allclose(
              output["attention_mask"],
              expected_output_attention_mask,
              atol=1e-4,
          )
      )
  
imports: import os
  import pickle
  import shutil
  import tempfile
  import unittest
  from transformers.feature_extraction_utils import BatchFeature
  from transformers.testing_utils import is_pretty_midi_available, is_torch_available, require_pretty_midi, require_torch
  from transformers.tokenization_utils import BatchEncoding
label_desc: Use image node_id 3 for calling the Pop2PianoTokenizerTest obj's underlying member method code with example usage: obj.test_call() without return types