Init estimation for regression. (#8272)

tests/python-gpu/test_from_cupy.py

@@ -224,5 +224,6 @@ Arrow specification.'''
         dtrain = dmatrix_from_cupy(
             np.float32, xgb.DeviceQuantileDMatrix, np.nan)
         with pytest.raises(xgb.core.XGBoostError):
-            xgb.train({'tree_method': 'gpu_hist', 'gpu_id': 1},
-                      dtrain, num_boost_round=10)
+            xgb.train(
+                {'tree_method': 'gpu_hist', 'gpu_id': 1}, dtrain, num_boost_round=10
+            )

tests/python-gpu/test_gpu_updaters.py

@@ -5,6 +5,7 @@ import numpy as np
 import pytest
 from hypothesis import assume, given, note, settings, strategies
 from xgboost.testing.params import cat_parameter_strategy, hist_parameter_strategy
+from xgboost.testing.updater import check_init_estimation
 
 import xgboost as xgb
 from xgboost import testing as tm
@@ -172,24 +173,25 @@ class TestGPUUpdaters:
         kCols = 100
 
         X = np.empty((kRows, kCols))
-        y = np.empty((kRows))
+        y = np.empty((kRows,))
 
         dtrain = xgb.DMatrix(X, y)
 
-        bst = xgb.train({'verbosity': 2,
-                         'tree_method': 'gpu_hist',
-                         'gpu_id': 0},
-                        dtrain,
-                        verbose_eval=True,
-                        num_boost_round=6,
-                        evals=[(dtrain, 'Train')])
+        bst = xgb.train(
+            {"verbosity": 2, "tree_method": "gpu_hist", "gpu_id": 0},
+            dtrain,
+            verbose_eval=True,
+            num_boost_round=6,
+            evals=[(dtrain, 'Train')]
+        )
 
         kRows = 100
         X = np.random.randn(kRows, kCols)
 
         dtest = xgb.DMatrix(X)
         predictions = bst.predict(dtest)
-        np.testing.assert_allclose(predictions, 0.5, 1e-6)
+        # non-distributed, 0.0 is returned due to base_score estimation with 0 gradient.
+        np.testing.assert_allclose(predictions, 0.0, 1e-6)
 
     @pytest.mark.mgpu
     @given(tm.dataset_strategy, strategies.integers(0, 10))
@@ -204,3 +206,6 @@ class TestGPUUpdaters:
     @pytest.mark.parametrize("weighted", [True, False])
     def test_adaptive(self, weighted) -> None:
         self.cputest.run_adaptive("gpu_hist", weighted)
+
+    def test_init_estimation(self) -> None:
+        check_init_estimation("gpu_hist")