[FIX] Backward compatibility: missing prediction_intervals (#1224)

Nixtla · Dec 16, 2024 · 2d0af6c · 2d0af6c
1 parent c6959f4
commit 2d0af6c
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Showing 2 changed files with 11 additions and 8 deletions.
diff --git a/nbs/core.ipynb b/nbs/core.ipynb
@@ -1546,9 +1546,12 @@
     "            \"id_col\": self.id_col,\n",
     "            \"time_col\": self.time_col,\n",
     "            \"target_col\": self.target_col,\n",
-    "            \"prediction_intervals\": self.prediction_intervals,\n",
-    "            \"_cs_df\": self._cs_df,  # conformity score\n",
     "        }\n",
+    "        for attr in ['prediction_intervals', '_cs_df']:\n",
+    "            # conformal prediction related attributes was not available < 1.7.6\n",
+    "            config_dict[attr] = getattr(self, attr, None)\n",
+    "            \n",
+    "\n",
     "        if save_dataset:\n",
     "            config_dict.update(\n",
     "                {\n",
@@ -1648,8 +1651,7 @@
     "            setattr(neuralforecast, attr, config_dict.get(attr, default))\n",
     "        # only restore attribute if available\n",
     "        for attr in ['prediction_intervals', '_cs_df']:\n",
-    "            if attr in config_dict.keys():\n",
-    "                setattr(neuralforecast, attr, config_dict[attr])\n",
+    "            setattr(neuralforecast, attr, config_dict.get(attr, None))\n",
     "\n",
     "        # Dataset\n",
     "        if dataset is not None:\n",

diff --git a/neuralforecast/core.py b/neuralforecast/core.py
@@ -1534,9 +1534,11 @@ def save(
             "id_col": self.id_col,
             "time_col": self.time_col,
             "target_col": self.target_col,
-            "prediction_intervals": self.prediction_intervals,
-            "_cs_df": self._cs_df,  # conformity score
         }
+        for attr in ["prediction_intervals", "_cs_df"]:
+            # conformal prediction related attributes was not available < 1.7.6
+            config_dict[attr] = getattr(self, attr, None)
+
         if save_dataset:
             config_dict.update(
                 {
@@ -1641,8 +1643,7 @@ def load(path, verbose=False, **kwargs):
             setattr(neuralforecast, attr, config_dict.get(attr, default))
         # only restore attribute if available
         for attr in ["prediction_intervals", "_cs_df"]:
-            if attr in config_dict.keys():
-                setattr(neuralforecast, attr, config_dict[attr])
+            setattr(neuralforecast, attr, config_dict.get(attr, None))
 
         # Dataset
         if dataset is not None: