code: def decode_predictions(preds):
      global CLASS_INDEX
      assert len(preds.shape) == 2 and preds.shape[1] == 1000
      if CLASS_INDEX is None:
          fpath = get_file(
              "imagenet_class_index.json",
              CLASS_INDEX_PATH,
              cache_subdir="models",
          )
          CLASS_INDEX = json.load(open(fpath))
      indices = np.argmax(preds, axis=-1)
      results = []
      for i in indices:
          results.append(CLASS_INDEX[str(i)])
      return results
  
imports: import numpy
  import json
  from keras.utils.data_utils import get_file
  from keras import backend
label_desc: Use image node_id 2 for calling a global function with example usage: decode_predictions(preds) and returns: results