code: def _prepare_directory(
      self,
      num_classes=2,
      nested_dirs=False,
      count=16,
      different_sequence_lengths=False,
  ):
      # Get a unique temp directory
      temp_dir = self.get_temp_dir()
  
      # Generate paths to class subdirectories
      paths = []
      for class_index in range(num_classes):
          class_directory = f"class_{class_index}"
          if nested_dirs:
              class_paths = [
                  class_directory,
                  os.path.join(class_directory, "subfolder_1"),
                  os.path.join(class_directory, "subfolder_2"),
                  os.path.join(
                      class_directory, "subfolder_1", "sub-subfolder"
                  ),
              ]
          else:
              class_paths = [class_directory]
          for path in class_paths:
              os.mkdir(os.path.join(temp_dir, path))
          paths += class_paths
  
      # Save audio samples to the paths
      i = 0
      for audio in self._get_audio_samples(
          count=count,
          different_sequence_lengths=different_sequence_lengths,
      ):
          path = paths[i % len(paths)]
          ext = "wav"
          filename = os.path.join(path, f"audio_{i}.{ext}")
          with open(os.path.join(temp_dir, filename), "wb") as f:
              f.write(audio.numpy())
          i += 1
      return temp_dir
  
imports: import os
  import numpy
  from keras import testing
  from keras.utils import audio_dataset_utils
  from keras.utils.module_utils import tensorflow
label_desc: Use image node_id 2 for calling the AudioDatasetFromDirectoryTest obj's underlying member method code with example usage: obj._prepare_directory(num_classes, nested_dirs, count, different_sequence_lengths) and returns: temp_dir