[python-package] fix mypy errors about validation sets in sklearn.py (#5724)

python-package/lightgbm/sklearn.py

@@ -756,7 +756,7 @@ class LGBMModel(_LGBMModelBase):
                             init_score=init_score, categorical_feature=categorical_feature,
                             params=params)
 
-        valid_sets = []
+        valid_sets: List[Dataset] = []
         if eval_set is not None:
 
             def _get_meta_data(collection, name, i):
@@ -1088,16 +1088,16 @@ class LGBMClassifier(_LGBMClassifierBase, LGBMModel):
             eval_metric = eval_metric_list
 
         # do not modify args, as it causes errors in model selection tools
-        valid_sets = None
+        valid_sets: Optional[List[Tuple]] = None
         if eval_set is not None:
             if isinstance(eval_set, tuple):
                 eval_set = [eval_set]
-            valid_sets = [None] * len(eval_set)
-            for i, (valid_x, valid_y) in enumerate(eval_set):
+            valid_sets = []
+            for valid_x, valid_y in eval_set:
                 if valid_x is X and valid_y is y:
-                    valid_sets[i] = (valid_x, _y)
+                    valid_sets.append((valid_x, _y))
                 else:
-                    valid_sets[i] = (valid_x, self._le.transform(valid_y))
+                    valid_sets.append((valid_x, self._le.transform(valid_y)))
 
         super().fit(
             X,