code: def classifyFileWrapper(inputFile, model_type, model_name):
      if not os.path.isfile(model_name):
          raise Exception("Input model_name not found!")
      if not os.path.isfile(inputFile):
          raise Exception("Input audio file not found!")
  
      [Result, P, classNames] = aT.file_classification(
          inputFile, model_name, model_type
      )
      print("{0:s}\t{1:s}".format("Class", "Probability"))
      for i, c in enumerate(classNames):
          print("{0:s}\t{1:.2f}".format(c, P[i]))
      print("Winner class: " + classNames[int(Result)])
  
imports: from __future__ import print_function
  import argparse
  import os
  import numpy
  import glob
  import matplotlib.pyplot
  import ShortTermFeatures
  import MidTermFeatures
  import audioTrainTest
  import audioSegmentation
  import audioVisualization
  import audioBasicIO
  import scipy.io.wavfile
  import matplotlib.patches
label_desc: Use image node_id 11 for calling a global function with example usage: classifyFileWrapper(inputFile, model_type, model_name) without return types