code: def fix_multiclass_predict_proba(y_proba,          # type: np.ndarray
                                   seen_classes,
                                   complete_classes
                                   ):
      # type: (...) -> np.ndarray
      
      assert set(complete_classes) >= set(seen_classes)
      y_proba_fixed = np.zeros(
          shape=(y_proba.shape[0], len(complete_classes)),
          dtype=y_proba.dtype,
      )
      class_mapping = np.searchsorted(complete_classes, seen_classes)
      y_proba_fixed[:, class_mapping] = y_proba
      return y_proba_fixed
docs: Add missing columns to predict_proba result.
  
      When a multiclass classifier is fit on a dataset which only contains
      a subset of possible classes its predict_proba result only has columns
      corresponding to seen classes. This function adds missing columns.