code: def _canonize_input(self, dataset):
          
          unpack = lambda x: x
          if isinstance(dataset, _tc.SArray):
              dataset = _tc.SFrame({self.feature: dataset})
          elif isinstance(dataset, _tc.Image):
              dataset = _tc.SFrame({self.feature: [dataset]})
              unpack = lambda x: x[0]
          return dataset, unpack
docs: Takes input and returns tuple of the input in canonical form (SFrame)
          along with an unpack callback function that can be applied to
          prediction results to "undo" the canonization.