code: def _make_text_predict_fn(self, labels, instance, column_to_explain):
          
  
          def _predict_fn(perturbed_text):
              predict_input = []
              for x in perturbed_text:
                  instance_copy = dict(instance)
                  instance_copy[column_to_explain] = x
                  predict_input.append(instance_copy)
  
              df = _local_predict.get_prediction_results(self._model_dir, predict_input,
                                                         self._headers, with_source=False)
              probs = _local_predict.get_probs_for_labels(labels, df)
              return np.asarray(probs)
  
          return _predict_fn
docs: Create a predict_fn that can be used by LIME text explainer.