FIX _validate_eval_set_Xy

Author: lorentzenchr

python-package/lightgbm/sklearn.py

@@ -500,6 +500,7 @@ def _validate_eval_set_Xy(eval_set, eval_X, eval_y):
     if eval_set is not None:
         msg = "The argument 'eval_set' is deprecated, use 'eval_X' and 'eval_y' instead."
         warnings.warn(msg, category=LGBMDeprecationWarning, stacklevel=2)
+        return eval_set
     if (eval_X is None) != (eval_y is None):
         raise ValueError("You must specify eval_X and eval_y, not just one of them.")
     if eval_set is None and eval_X is not None:
@@ -511,6 +512,7 @@ def _validate_eval_set_Xy(eval_set, eval_X, eval_y):
             eval_set = (eval_X, eval_y)
         else:
             eval_set = list(zip(eval_X, eval_y))
+    return eval_set
 
 
 class LGBMModel(_LGBMModelBase):

tests/python_package_test/test_sklearn.py

@@ -2053,7 +2053,7 @@ def test_eval_set_deprecation():
     gbm = lgb.LGBMRegressor()
     msg = "The argument 'eval_set' is deprecated.*"
     with pytest.warns(LGBMDeprecationWarning, match=msg):
-        gbm.fit(X_train, y_train, eval_set=(X_test, y_test))
+        gbm.fit(X_train, y_train, eval_set=[(X_test, y_test)])
 
 
 def test_eval_X_eval_y_eval_set_equivalence():
@@ -2062,7 +2062,7 @@ def test_eval_X_eval_y_eval_set_equivalence():
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)
     cbs = [lgb.early_stopping(2)]
     gbm1 = lgb.LGBMRegressor()
-    gbm1.fit(X_train, y_train, eval_set=(X_test, y_test), callbacks=cbs)
+    gbm1.fit(X_train, y_train, eval_set=[(X_test, y_test)], callbacks=cbs)
     gbm2 = lgb.LGBMRegressor()
     gbm2.fit(X_train, y_train, eval_X=X_test, eval_y=y_test, callbacks=cbs)
     np.testing.assert_allclose(gbm1.predict(X), gbm2.predict(X))