def METHOD_NAME(wav, labels, graph, input_name, output_name, how_many_labels):
  """Loads the model and labels, and runs the inference to print predictions."""
  if not wav or not tf.io.gfile.exists(wav):
    tf.compat.v1.logging.fatal('Audio file does not exist %s', wav)
  if not labels or not tf.io.gfile.exists(labels):
    tf.compat.v1.logging.fatal('Labels file does not exist %s', labels)
  if not graph or not tf.io.gfile.exists(graph):
    tf.compat.v1.logging.fatal('Graph file does not exist %s', graph)
  labels_list = load_labels(labels)
  # load graph, which is stored in the default session
  load_graph(graph)
  with open(wav, 'rb') as wav_file:
    wav_data = wav_file.read()
  run_graph(wav_data, labels_list, input_name, output_name, how_many_labels)