Cleanup Python GPU tests. (#9934)

* Cleanup Python GPU tests.

- Remove the use of `gpu_hist` and `gpu_id` in cudf/cupy tests.
- Move base margin test into the testing directory.

tests/python/test_dmatrix.py

@@ -1,6 +1,5 @@
 import csv
 import os
-import sys
 import tempfile
 
 import numpy as np
@@ -12,59 +11,12 @@ from scipy.sparse import csr_matrix, rand
 import xgboost as xgb
 from xgboost import testing as tm
 from xgboost.core import DataSplitMode
-from xgboost.testing.data import np_dtypes
-
-rng = np.random.RandomState(1)
+from xgboost.testing.data import np_dtypes, run_base_margin_info
 
 dpath = "demo/data/"
 rng = np.random.RandomState(1994)
 
 
-def set_base_margin_info(DType, DMatrixT, tm: str):
-    rng = np.random.default_rng()
-    X = DType(rng.normal(0, 1.0, size=100).astype(np.float32).reshape(50, 2))
-    if hasattr(X, "iloc"):
-        y = X.iloc[:, 0]
-    else:
-        y = X[:, 0]
-    base_margin = X
-    # no error at set
-    Xy = DMatrixT(X, y, base_margin=base_margin)
-    # Error at train, caused by check in predictor.
-    with pytest.raises(ValueError, match=r".*base_margin.*"):
-        xgb.train({"tree_method": tm}, Xy)
-
-    if not hasattr(X, "iloc"):
-        # column major matrix
-        got = DType(Xy.get_base_margin().reshape(50, 2))
-        assert (got == base_margin).all()
-
-        assert base_margin.T.flags.c_contiguous is False
-        assert base_margin.T.flags.f_contiguous is True
-        Xy.set_info(base_margin=base_margin.T)
-        got = DType(Xy.get_base_margin().reshape(2, 50))
-        assert (got == base_margin.T).all()
-
-        # Row vs col vec.
-        base_margin = y
-        Xy.set_base_margin(base_margin)
-        bm_col = Xy.get_base_margin()
-        Xy.set_base_margin(base_margin.reshape(1, base_margin.size))
-        bm_row = Xy.get_base_margin()
-        assert (bm_row == bm_col).all()
-
-        # type
-        base_margin = base_margin.astype(np.float64)
-        Xy.set_base_margin(base_margin)
-        bm_f64 = Xy.get_base_margin()
-        assert (bm_f64 == bm_col).all()
-
-        # too many dimensions
-        base_margin = X.reshape(2, 5, 2, 5)
-        with pytest.raises(ValueError, match=r".*base_margin.*"):
-            Xy.set_base_margin(base_margin)
-
-
 class TestDMatrix:
     def test_warn_missing(self):
         from xgboost import data
@@ -417,8 +369,8 @@ class TestDMatrix:
         )
         np.testing.assert_equal(np.array(Xy.feature_types), np.array(feature_types))
 
-    def test_base_margin(self):
-        set_base_margin_info(np.asarray, xgb.DMatrix, "hist")
+    def test_base_margin(self) -> None:
+        run_base_margin_info(np.asarray, xgb.DMatrix, "cpu")
 
     @given(
         strategies.integers(0, 1000),

tests/python/test_with_modin.py

@@ -1,9 +1,9 @@
 import numpy as np
 import pytest
-from test_dmatrix import set_base_margin_info
 
 import xgboost as xgb
 from xgboost import testing as tm
+from xgboost.testing.data import run_base_margin_info
 
 try:
     import modin.pandas as md
@@ -145,4 +145,4 @@ class TestModin:
         np.testing.assert_array_equal(data.get_weight(), w)
 
     def test_base_margin(self):
-        set_base_margin_info(md.DataFrame, xgb.DMatrix, "hist")
+        run_base_margin_info(md.DataFrame, xgb.DMatrix, "cpu")

tests/python/test_with_pandas.py

@@ -1,14 +1,12 @@
-import sys
 from typing import Type
 
 import numpy as np
 import pytest
-from test_dmatrix import set_base_margin_info
 
 import xgboost as xgb
 from xgboost import testing as tm
 from xgboost.core import DataSplitMode
-from xgboost.testing.data import pd_arrow_dtypes, pd_dtypes
+from xgboost.testing.data import pd_arrow_dtypes, pd_dtypes, run_base_margin_info
 
 try:
     import pandas as pd
@@ -336,7 +334,7 @@ class TestPandas:
         np.testing.assert_array_equal(data.get_weight(), w)
 
     def test_base_margin(self):
-        set_base_margin_info(pd.DataFrame, xgb.DMatrix, "hist")
+        run_base_margin_info(pd.DataFrame, xgb.DMatrix, "cpu")
 
     def test_cv_as_pandas(self):
         dm, _ = tm.load_agaricus(__file__)