fix: LightGBM 4.0+ compatibility for early_stopping_rounds=None

qlib/contrib/model/gbdt.py

@@ -68,19 +68,26 @@ def fit(
             evals_result = {}  # in case of unsafety of Python default values
         ds_l = self._prepare_data(dataset, reweighter)
         ds, names = list(zip(*ds_l))
-        early_stopping_callback = lgb.early_stopping(
-            self.early_stopping_rounds if early_stopping_rounds is None else early_stopping_rounds
-        )
+
+        # Build callbacks list
+        callbacks = []
+
+        # Only add early_stopping callback if rounds is not None (LightGBM 4.0+ doesn't accept None)
+        early_stop_rounds = self.early_stopping_rounds if early_stopping_rounds is None else early_stopping_rounds
+        if early_stop_rounds is not None:
+            callbacks.append(lgb.early_stopping(early_stop_rounds))
+
         # NOTE: if you encounter error here. Please upgrade your lightgbm
-        verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
-        evals_result_callback = lgb.record_evaluation(evals_result)
+        callbacks.append(lgb.log_evaluation(period=verbose_eval))
+        callbacks.append(lgb.record_evaluation(evals_result))
+
         self.model = lgb.train(
             self.params,
             ds[0],  # training dataset
             num_boost_round=self.num_boost_round if num_boost_round is None else num_boost_round,
             valid_sets=ds,
             valid_names=names,
-            callbacks=[early_stopping_callback, verbose_eval_callback, evals_result_callback],
+            callbacks=callbacks,
             **kwargs,
         )
         for k in names:

qlib/contrib/model/highfreq_gdbt_model.py

@@ -124,16 +124,21 @@ def fit(
         if evals_result is None:
             evals_result = dict()
         dtrain, dvalid = self._prepare_data(dataset)
-        early_stopping_callback = lgb.early_stopping(early_stopping_rounds)
-        verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
-        evals_result_callback = lgb.record_evaluation(evals_result)
+
+        # Build callbacks list
+        callbacks = []
+        if early_stopping_rounds is not None:
+            callbacks.append(lgb.early_stopping(early_stopping_rounds))
+        callbacks.append(lgb.log_evaluation(period=verbose_eval))
+        callbacks.append(lgb.record_evaluation(evals_result))
+
         self.model = lgb.train(
             self.params,
             dtrain,
             num_boost_round=num_boost_round,
             valid_sets=[dtrain, dvalid],
             valid_names=["train", "valid"],
-            callbacks=[early_stopping_callback, verbose_eval_callback, evals_result_callback],
+            callbacks=callbacks,
         )
         evals_result["train"] = list(evals_result["train"].values())[0]
         evals_result["valid"] = list(evals_result["valid"].values())[0]

qlib/contrib/rolling/ddgda.py

@@ -241,7 +241,9 @@ def _dump_meta_ipt(self):
         sim_task = replace_task_handler_with_cache(sim_task, self.working_dir)
 
         if self.sim_task_model == "gbdt":
-            sim_task["model"].setdefault("kwargs", {}).update({"early_stopping_rounds": None, "num_boost_round": 150})
+            sim_task["model"].setdefault("kwargs", {}).update({"num_boost_round": 150})
+            # Don't set early_stopping_rounds to disable it (LightGBM 4.0+ doesn't accept None)
+            sim_task["model"]["kwargs"].pop("early_stopping_rounds", None)
 
         exp_name_sim = f"data_sim_s{self.step}"