code: def test_padding(self, max_length=50):
      def _input_values_have_equal_length(input_values):
          length = len(input_values[0])
          for input_values_slice in input_values[1:]:
              if len(input_values_slice) != length:
                  return False
          return True
  
      def _input_values_are_equal(input_values_1, input_values_2):
          if len(input_values_1) != len(input_values_2):
              return False
  
          for input_values_slice_1, input_values_slice_2 in zip(
              input_values_1, input_values_2
          ):
              if not np.allclose(
                  np.asarray(input_values_slice_1),
                  np.asarray(input_values_slice_2),
                  atol=1e-3,
              ):
                  return False
          return True
  
      tokenizer = self.get_tokenizer()
      speech_inputs = [
          floats_list((1, x))[0] for x in range(800, 1400, 200)
      ]
  
      input_values_1 = tokenizer(speech_inputs).input_values
      input_values_2 = tokenizer(
          speech_inputs, padding="longest"
      ).input_values
      input_values_3 = tokenizer(
          speech_inputs, padding="longest", max_length=1600
      ).input_values
  
      self.assertFalse(_input_values_have_equal_length(input_values_1))
      self.assertTrue(_input_values_have_equal_length(input_values_2))
      self.assertTrue(_input_values_have_equal_length(input_values_3))
      self.assertTrue(
          _input_values_are_equal(input_values_2, input_values_3)
      )
      self.assertTrue(len(input_values_1[0]) == 800)
      self.assertTrue(len(input_values_2[0]) == 1200)
      # padding should be 0.0
      self.assertTrue(
          abs(sum(np.asarray(input_values_2[0])[800:])) < 1e-3
      )
      self.assertTrue(
          abs(sum(np.asarray(input_values_2[1])[1000:])) < 1e-3
      )
  
      input_values_4 = tokenizer(
          speech_inputs, padding="max_length"
      ).input_values
      input_values_5 = tokenizer(
          speech_inputs, padding="max_length", max_length=1600
      ).input_values
  
      self.assertTrue(
          _input_values_are_equal(input_values_1, input_values_4)
      )
      self.assertEqual(input_values_5.shape, (3, 1600))
      # padding should be 0.0
      self.assertTrue(
          abs(sum(np.asarray(input_values_5[0])[800:1200])) < 1e-3
      )
  
      input_values_6 = tokenizer(
          speech_inputs, pad_to_multiple_of=500
      ).input_values
      input_values_7 = tokenizer(
          speech_inputs, padding="longest", pad_to_multiple_of=500
      ).input_values
      input_values_8 = tokenizer(
          speech_inputs,
          padding="max_length",
          pad_to_multiple_of=500,
          max_length=2400,
      ).input_values
  
      self.assertTrue(
          _input_values_are_equal(input_values_1, input_values_6)
      )
      self.assertEqual(input_values_7.shape, (3, 1500))
      self.assertEqual(input_values_8.shape, (3, 2500))
      # padding should be 0.0
      self.assertTrue(
          abs(sum(np.asarray(input_values_7[0])[800:])) < 1e-3
      )
      self.assertTrue(
          abs(sum(np.asarray(input_values_7[1])[1000:])) < 1e-3
      )
      self.assertTrue(
          abs(sum(np.asarray(input_values_7[2])[1200:])) < 1e-3
      )
      self.assertTrue(
          abs(sum(np.asarray(input_values_8[0])[800:])) < 1e-3
      )
      self.assertTrue(
          abs(sum(np.asarray(input_values_8[1])[1000:])) < 1e-3
      )
      self.assertTrue(
          abs(sum(np.asarray(input_values_8[2])[1200:])) < 1e-3
      )
  
imports: import inspect
  import json
  import os
  import random
  import shutil
  import tempfile
  import unittest
  import numpy
  from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, AddedToken, Wav2Vec2Config, Wav2Vec2CTCTokenizer, Wav2Vec2Tokenizer
  from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES, Wav2Vec2CTCTokenizerOutput
  from transformers.testing_utils import require_torch, slow
  from ...test_tokenization_common import TokenizerTesterMixin
label_desc: Use image node_id 7 for calling the Wav2Vec2TokenizerTest obj's underlying member method code with example usage: obj.test_padding(max_length) and returns: True, True, False, False, False