Disable pytest-timeout for now. (#8348)

tests/python-gpu/test_gpu_linear.py

@@ -1,12 +1,15 @@
 import sys
-from hypothesis import strategies, given, settings, assume, note
+
 import pytest
+from hypothesis import assume, given, note, settings, strategies
+
 import xgboost as xgb
+from xgboost import testing
+
 sys.path.append("tests/python")
 import testing as tm
 
-
-pytestmark = pytest.mark.timeout(10)
+pytestmark = testing.timeout(10)
 
 parameter_strategy = strategies.fixed_dictionaries({
     'booster': strategies.just('gblinear'),

tests/python-gpu/test_gpu_pickling.py

@@ -1,21 +1,23 @@
 '''Test model IO with pickle.'''
-import pickle
-import numpy as np
-import subprocess
-import os
-import sys
 import json
+import os
+import pickle
+import subprocess
+import sys
+
+import numpy as np
 import pytest
+
 import xgboost as xgb
-from xgboost import XGBClassifier
+from xgboost import XGBClassifier, testing
 
 sys.path.append("tests/python")
 import testing as tm
 
 model_path = './model.pkl'
 
+pytestmark = testing.timeout(30)
 
-pytestmark = pytest.mark.timeout(30)
 
 def build_dataset():
     N = 10

tests/python-gpu/test_gpu_prediction.py

@@ -1,11 +1,12 @@
 import sys
-import pytest
 
 import numpy as np
-import xgboost as xgb
+import pytest
+from hypothesis import assume, given, settings, strategies
 from xgboost.compat import PANDAS_INSTALLED
 
-from hypothesis import given, strategies, assume, settings
+import xgboost as xgb
+from xgboost import testing
 
 if PANDAS_INSTALLED:
     from hypothesis.extra.pandas import column, data_frames, range_indexes
@@ -16,8 +17,8 @@ else:
 
 sys.path.append("tests/python")
 import testing as tm
+from test_predict import run_predict_leaf  # noqa
 from test_predict import run_threaded_predict  # noqa
-from test_predict import run_predict_leaf      # noqa
 
 rng = np.random.RandomState(1994)
 
@@ -32,7 +33,8 @@ predict_parameter_strategy = strategies.fixed_dictionaries({
     'num_parallel_tree': strategies.sampled_from([1, 4]),
 })
 
-pytestmark = pytest.mark.timeout(20)
+pytestmark = testing.timeout(20)
+
 
 class TestGPUPredict:
     def test_predict(self):

tests/python-gpu/test_gpu_ranking.py

@@ -1,17 +1,21 @@
-import numpy as np
-import xgboost
-import os
 import itertools
+import os
 import shutil
+import sys
 import urllib.request
 import zipfile
-import sys
-import pytest
+
+import numpy as np
+
+import xgboost
+from xgboost import testing
+
 sys.path.append("tests/python")
 
-import testing as tm            # noqa
+import testing as tm  # noqa
+
+pytestmark = testing.timeout(10)
 
-pytestmark = pytest.mark.timeout(10)
 
 class TestRanking:
     @classmethod

tests/python-gpu/test_gpu_updaters.py

@@ -1,15 +1,18 @@
-from typing import Dict, Any
-import numpy as np
 import sys
+from typing import Any, Dict
+
+import numpy as np
 import pytest
+from hypothesis import assume, given, note, settings, strategies
+
 import xgboost as xgb
-from hypothesis import given, strategies, assume, settings, note
+from xgboost import testing
 
 sys.path.append("tests/python")
-import testing as tm
 import test_updaters as test_up
+import testing as tm
 
-pytestmark = pytest.mark.timeout(30)
+pytestmark = testing.timeout(30)
 
 parameter_strategy = strategies.fixed_dictionaries({
     'max_depth': strategies.integers(0, 11),

tests/python/test_data_iterator.py

@@ -1,12 +1,15 @@
-import xgboost as xgb
-from xgboost.data import SingleBatchInternalIter as SingleBatch
 import numpy as np
-from testing import IteratorForTest, non_increasing, make_batches
 import pytest
-from hypothesis import given, strategies, settings
+from hypothesis import given, settings, strategies
 from scipy.sparse import csr_matrix
+from testing import IteratorForTest, make_batches, non_increasing
+from xgboost.data import SingleBatchInternalIter as SingleBatch
+
+import xgboost as xgb
+from xgboost import testing
+
+pytestmark = testing.timeout(30)
 
-pytestmark = pytest.mark.timeout(30)
 
 def test_single_batch(tree_method: str = "approx") -> None:
     from sklearn.datasets import load_breast_cancer

tests/python/test_demos.py

@@ -1,10 +1,13 @@
 import os
 import subprocess
-import pytest
-import testing as tm
 import sys
 
-pytestmark = pytest.mark.timeout(30)
+import pytest
+import testing as tm
+
+from xgboost import testing
+
+pytestmark = testing.timeout(30)
 
 ROOT_DIR = tm.PROJECT_ROOT
 DEMO_DIR = os.path.join(ROOT_DIR, 'demo')

tests/python/test_linear.py

@@ -1,9 +1,11 @@
 import testing as tm
-import pytest
-from hypothesis import strategies, given, settings, note
-import xgboost as xgb
+from hypothesis import given, note, settings, strategies
+
+import xgboost as xgb
+from xgboost import testing
+
+pytestmark = testing.timeout(10)
 
-pytestmark = pytest.mark.timeout(10)
 
 parameter_strategy = strategies.fixed_dictionaries({
     'booster': strategies.just('gblinear'),

tests/python/test_openmp.py

@@ -1,14 +1,16 @@
 import os
-import tempfile
 import subprocess
+import tempfile
 
-import xgboost as xgb
 import numpy as np
 import pytest
-
 import testing as tm
 
-pytestmark = pytest.mark.timeout(10)
+import xgboost as xgb
+from xgboost import testing
+
+pytestmark = testing.timeout(10)
+
 
 class TestOMP:
     def test_omp(self):

tests/python/test_spark/test_spark_local.py

@@ -9,6 +9,7 @@ import pytest
 import testing as tm
 
 import xgboost as xgb
+from xgboost import testing
 
 if tm.no_spark()["condition"]:
     pytest.skip(msg=tm.no_spark()["reason"], allow_module_level=True)
@@ -37,7 +38,7 @@ from .utils import SparkTestCase
 
 logging.getLogger("py4j").setLevel(logging.INFO)
 
-pytestmark = pytest.mark.timeout(60)
+pytestmark = testing.timeout(60)
 
 
 class XgboostLocalTest(SparkTestCase):

tests/python/test_with_dask.py

@@ -29,6 +29,7 @@ from test_with_sklearn import run_data_initialization, run_feature_weights
 from xgboost.data import _is_cudf_df
 
 import xgboost as xgb
+from xgboost import testing
 
 if sys.platform.startswith("win"):
     pytest.skip("Skipping dask tests on Windows", allow_module_level=True)
@@ -44,7 +45,7 @@ from xgboost.dask import DaskDMatrix
 
 dask.config.set({"distributed.scheduler.allowed-failures": False})
 
-pytestmark = pytest.mark.timeout(30)
+pytestmark = testing.timeout(30)
 
 if hasattr(HealthCheck, 'function_scoped_fixture'):
     suppress = [HealthCheck.function_scoped_fixture]

tests/python/test_with_sklearn.py

@@ -1,20 +1,20 @@
-from typing import Callable, Optional
 import collections
 import importlib.util
-import numpy as np
-import xgboost as xgb
-import testing as tm
-import tempfile
-import os
-import shutil
-import pytest
 import json
+import os
+import tempfile
+from typing import Callable, Optional
+
+import numpy as np
+import pytest
+import testing as tm
+from sklearn.utils.estimator_checks import parametrize_with_checks
+
+import xgboost as xgb
+from xgboost import testing
 
 rng = np.random.RandomState(1994)
-
-pytestmark = [pytest.mark.skipif(**tm.no_sklearn()), pytest.mark.timeout(30)]
-
-from sklearn.utils.estimator_checks import parametrize_with_checks
+pytestmark = [pytest.mark.skipif(**tm.no_sklearn()), testing.timeout(30)]
 
 
 def test_binary_classification():