Test.

tests/python-gpu/test_gpu_updaters.py

@@ -61,6 +61,9 @@ def test_gpu_hist(self, param, num_rounds, dataset):
     def test_categorical(self, rows, cols, rounds, cats):
         self.cputest.run_categorical_basic(rows, cols, rounds, cats, "gpu_hist")
 
+    def test_max_cat(self) -> None:
+        self.cputest.run_max_cat("gpu_hist")
+
     def test_categorical_32_cat(self):
         '''32 hits the bound of integer bitset, so special test'''
         rows = 1000

tests/python/test_updaters.py

@@ -1,3 +1,5 @@
+from random import choice
+from string import ascii_lowercase
 import testing as tm
 import pytest
 import xgboost as xgb
@@ -169,6 +171,30 @@ def run_invalid_category(self, tree_method: str) -> None:
 
     def test_invalid_category(self) -> None:
         self.run_invalid_category("approx")
+        self.run_invalid_category("hist")
+
+    def run_max_cat(self, tree_method: str) -> None:
+        """Test data with size smaller than number of categories."""
+        import pandas as pd
+        n_cat = 100
+        n = 5
+        X = pd.Series(
+            ["".join(choice(ascii_lowercase) for i in range(3)) for i in range(n_cat)],
+            dtype="category",
+        )[:n].to_frame()
+
+        reg = xgb.XGBRegressor(
+            enable_categorical=True,
+            tree_method=tree_method,
+            n_estimators=10,
+        )
+        y = pd.Series(range(n))
+        reg.fit(X=X, y=y, eval_set=[(X, y)])
+        assert tm.non_increasing(reg.evals_result()["validation_0"]["rmse"])
+
+    @pytest.mark.parametrize("tree_method", ["hist", "approx"])
+    def test_max_cat(self, tree_method) -> None:
+        self.run_max_cat(tree_method)
 
     def run_categorical_basic(self, rows, cols, rounds, cats, tree_method):
         onehot, label = tm.make_categorical(rows, cols, cats, True)