[python] fix the bug when use different params with reference (#2907)

* fix the bug when use different params with reference

* fix

* Update basic.py

* Apply suggestions from code review
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Update basic.py

* add test

* Apply suggestions from code review

* added asserts in test
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: StrikerRUS <nekit94-12@hotmail.com>

python-package/lightgbm/basic.py

@@ -1097,6 +1097,10 @@ class Dataset(object):
         """
         if self.handle is None:
             if self.reference is not None:
+                reference_params = self.reference.get_params()
+                if self.get_params() != reference_params:
+                    warnings.warn('Overriding the parameters from Reference Dataset.')
+                    self._update_params(reference_params)
                 if self.used_indices is None:
                     # create valid
                     self._lazy_init(self.data, label=self.label, reference=self.reference,
@@ -1222,6 +1226,8 @@ class Dataset(object):
         return self
 
     def _update_params(self, params):
+        if not params:
+            return self
         params = copy.deepcopy(params)
 
         def update():

tests/python_package_test/test_engine.py

@@ -1958,6 +1958,18 @@ class TestEngine(unittest.TestCase):
             with np.testing.assert_raises_regex(lgb.basic.LightGBMError, err_msg):
                 lgb.train(new_params, lgb_data, num_boost_round=3)
 
+    def test_dataset_params_with_reference(self):
+        default_params = {"max_bin": 100}
+        X = np.random.random((100, 2))
+        y = np.random.random(100)
+        X_val = np.random.random((100, 2))
+        y_val = np.random.random(100)
+        lgb_train = lgb.Dataset(X, y, params=default_params, free_raw_data=False).construct()
+        lgb_val = lgb.Dataset(X_val, y_val, reference=lgb_train, free_raw_data=False).construct()
+        self.assertDictEqual(lgb_train.get_params(), default_params)
+        self.assertDictEqual(lgb_val.get_params(), default_params)
+        model = lgb.train(default_params, lgb_train, valid_sets=[lgb_val])
+
     def test_extra_trees(self):
         # check extra trees increases regularization
         X, y = load_boston(True)