text: import argparse
  import load_data
  import model_fuc
  
  parser = argparse.ArgumentParser(description = 'Predict the image using trained model')
  parser.add_argument('input', nargs = '?', action = "store", default = "flowers/test/1/image_06752.jpg")
  parser.add_argument('checkpoint', nargs = '?', action = "store", default = "./checkpoint.pth")
  parser.add_argument('--top_k', dest = 'top_k', nargs = '?', action = "store", type = int, default = 3)
  parser.add_argument('--category_names', dest = 'cat', nargs = '?', action = "store", default = 'cat_to_name.json')
  parser.add_argument('--gpu', dest = 'gpu', nargs='?', action="store", default='GPU')
  
  pa = parser.parse_args()
  input_path = pa.input
  checkpoint = pa.checkpoint
  topk = pa.top_k
  cat = pa.cat
  gpu = pa.gpu
  
  model =  model_fuc.load_model(path = checkpoint)
  flower_name, prob = model_fuc.predict(input_path, model, topk, power = gpu, category_names = cat)
  print(flower_name)
  print(prob)
  
  
  
  
  
  