fix(gbdt): correct dtrain assignment in finetune() to use Dataset instead of tuple (microsoft#2049)

Author: SunsetWolf

qlib/contrib/model/gbdt.py

@@ -51,7 +51,7 @@ def _prepare_data(self, dataset: DatasetH, reweighter=None) -> List[Tuple[lgb.Da
                     w = reweighter.reweight(df)
                 else:
                     raise ValueError("Unsupported reweighter type.")
-                ds_l.append((lgb.Dataset(x.values, label=y, weight=w), key))
+                ds_l.append((lgb.Dataset(x.values, label=y, weight=w, free_raw_data=False), key))
         return ds_l
 
     def fit(
@@ -109,8 +109,10 @@ def finetune(self, dataset: DatasetH, num_boost_round=10, verbose_eval=20, rewei
             verbose level
         """
         # Based on existing model and finetune by train more rounds
-        dtrain, _ = self._prepare_data(dataset, reweighter)  # pylint: disable=W0632
-        if dtrain.empty:
+        ds_l = self._prepare_data(dataset, reweighter)
+        dtrain, _ = ds_l[0]
+
+        if dtrain.construct().num_data() == 0:
             raise ValueError("Empty data from dataset, please check your dataset config.")
         verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
         self.model = lgb.train(