Fix different number of features in gpu_hist evaluator. (#8754)

tests/python-gpu/test_gpu_interaction_constraints.py

@@ -1,6 +1,9 @@
 import sys
 
 import numpy as np
+import pandas as pd
+
+import xgboost as xgb
 
 sys.path.append("tests/python")
 # Don't import the test class, otherwise they will run twice.
@@ -13,7 +16,34 @@ class TestGPUInteractionConstraints:
     cputest = test_ic.TestInteractionConstraints()
 
     def test_interaction_constraints(self):
-        self.cputest.run_interaction_constraints(tree_method='gpu_hist')
+        self.cputest.run_interaction_constraints(tree_method="gpu_hist")
 
     def test_training_accuracy(self):
-        self.cputest.training_accuracy(tree_method='gpu_hist')
+        self.cputest.training_accuracy(tree_method="gpu_hist")
+
+    # case where different number of features can occur in the evaluator
+    def test_issue_8730(self):
+        X = pd.DataFrame(
+            zip(range(0, 100), range(200, 300), range(300, 400), range(400, 500)),
+            columns=["A", "B", "C", "D"],
+        )
+        y = np.array([*([0] * 50), *([1] * 50)])
+        dm = xgb.DMatrix(X, label=y)
+
+        params = {
+            "eta": 0.16095019509249486,
+            "min_child_weight": 1,
+            "subsample": 0.688567929338029,
+            "colsample_bynode": 0.7,
+            "gamma": 5.666579817418348e-06,
+            "lambda": 0.14943712232059794,
+            "grow_policy": "depthwise",
+            "max_depth": 3,
+            "tree_method": "gpu_hist",
+            "interaction_constraints": [["A", "B"], ["B", "D", "C"], ["C", "D"]],
+            "objective": "count:poisson",
+            "eval_metric": "poisson-nloglik",
+            "verbosity": 0,
+        }
+
+        xgb.train(params, dm, num_boost_round=100)