Disable pytest-timeout for now. (#8348)
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@ -2,7 +2,7 @@
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import socket
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from platform import system
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from typing import TypedDict
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from typing import Any, TypedDict
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PytestSkip = TypedDict("PytestSkip", {"condition": bool, "reason": str})
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@ -39,3 +39,26 @@ def has_ipv6() -> bool:
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def skip_ipv6() -> PytestSkip:
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"""PyTest skip mark for IPv6."""
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return {"condition": not has_ipv6(), "reason": "IPv6 is required to be enabled."}
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def timeout(sec: int, *args: Any, enable: bool = False, **kwargs: Any) -> Any:
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"""Make a pytest mark for the `pytest-timeout` package.
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Parameters
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----------
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sec :
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Timeout seconds.
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enable :
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Control whether timeout should be applied, used for debugging.
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Returns
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-------
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pytest.mark.timeout
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"""
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import pytest # pylint: disable=import-error
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# This is disabled for now due to regression caused by conflicts between federated
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# learning build and the CI container environment.
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if enable:
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return pytest.mark.timeout(sec, *args, **kwargs)
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return pytest.mark.timeout(None, *args, **kwargs)
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@ -1,12 +1,15 @@
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import sys
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from hypothesis import strategies, given, settings, assume, note
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import pytest
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from hypothesis import assume, given, note, settings, strategies
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import xgboost as xgb
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from xgboost import testing
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sys.path.append("tests/python")
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import testing as tm
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pytestmark = pytest.mark.timeout(10)
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pytestmark = testing.timeout(10)
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parameter_strategy = strategies.fixed_dictionaries({
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'booster': strategies.just('gblinear'),
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@ -1,21 +1,23 @@
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'''Test model IO with pickle.'''
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import pickle
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import numpy as np
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import subprocess
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import os
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import sys
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import json
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import os
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import pickle
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import subprocess
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import sys
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import numpy as np
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import pytest
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import xgboost as xgb
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from xgboost import XGBClassifier
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from xgboost import XGBClassifier, testing
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sys.path.append("tests/python")
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import testing as tm
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model_path = './model.pkl'
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pytestmark = testing.timeout(30)
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pytestmark = pytest.mark.timeout(30)
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def build_dataset():
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N = 10
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@ -1,11 +1,12 @@
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import sys
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import pytest
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import numpy as np
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import xgboost as xgb
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import pytest
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from hypothesis import assume, given, settings, strategies
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from xgboost.compat import PANDAS_INSTALLED
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from hypothesis import given, strategies, assume, settings
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import xgboost as xgb
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from xgboost import testing
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if PANDAS_INSTALLED:
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from hypothesis.extra.pandas import column, data_frames, range_indexes
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@ -16,8 +17,8 @@ else:
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sys.path.append("tests/python")
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import testing as tm
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from test_predict import run_predict_leaf # noqa
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from test_predict import run_threaded_predict # noqa
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from test_predict import run_predict_leaf # noqa
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rng = np.random.RandomState(1994)
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@ -32,7 +33,8 @@ predict_parameter_strategy = strategies.fixed_dictionaries({
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'num_parallel_tree': strategies.sampled_from([1, 4]),
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})
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pytestmark = pytest.mark.timeout(20)
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pytestmark = testing.timeout(20)
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class TestGPUPredict:
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def test_predict(self):
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@ -1,17 +1,21 @@
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import numpy as np
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import xgboost
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import os
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import itertools
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import os
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import shutil
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import sys
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import urllib.request
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import zipfile
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import sys
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import pytest
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import numpy as np
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import xgboost
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from xgboost import testing
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sys.path.append("tests/python")
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import testing as tm # noqa
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import testing as tm # noqa
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pytestmark = testing.timeout(10)
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pytestmark = pytest.mark.timeout(10)
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class TestRanking:
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@classmethod
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@ -1,15 +1,18 @@
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from typing import Dict, Any
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import numpy as np
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import sys
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from typing import Any, Dict
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import numpy as np
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import pytest
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from hypothesis import assume, given, note, settings, strategies
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import xgboost as xgb
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from hypothesis import given, strategies, assume, settings, note
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from xgboost import testing
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sys.path.append("tests/python")
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import testing as tm
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import test_updaters as test_up
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import testing as tm
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pytestmark = pytest.mark.timeout(30)
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pytestmark = testing.timeout(30)
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parameter_strategy = strategies.fixed_dictionaries({
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'max_depth': strategies.integers(0, 11),
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@ -1,12 +1,15 @@
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import xgboost as xgb
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from xgboost.data import SingleBatchInternalIter as SingleBatch
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import numpy as np
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from testing import IteratorForTest, non_increasing, make_batches
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import pytest
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from hypothesis import given, strategies, settings
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from hypothesis import given, settings, strategies
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from scipy.sparse import csr_matrix
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from testing import IteratorForTest, make_batches, non_increasing
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from xgboost.data import SingleBatchInternalIter as SingleBatch
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import xgboost as xgb
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from xgboost import testing
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pytestmark = testing.timeout(30)
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pytestmark = pytest.mark.timeout(30)
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def test_single_batch(tree_method: str = "approx") -> None:
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from sklearn.datasets import load_breast_cancer
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@ -1,10 +1,13 @@
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import os
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import subprocess
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import pytest
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import testing as tm
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import sys
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pytestmark = pytest.mark.timeout(30)
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import pytest
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import testing as tm
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from xgboost import testing
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pytestmark = testing.timeout(30)
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ROOT_DIR = tm.PROJECT_ROOT
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DEMO_DIR = os.path.join(ROOT_DIR, 'demo')
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@ -1,9 +1,11 @@
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import testing as tm
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import pytest
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from hypothesis import strategies, given, settings, note
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import xgboost as xgb
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from hypothesis import given, note, settings, strategies
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import xgboost as xgb
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from xgboost import testing
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pytestmark = testing.timeout(10)
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pytestmark = pytest.mark.timeout(10)
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parameter_strategy = strategies.fixed_dictionaries({
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'booster': strategies.just('gblinear'),
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@ -1,14 +1,16 @@
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import os
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import tempfile
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import subprocess
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import tempfile
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import xgboost as xgb
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import numpy as np
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import pytest
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import testing as tm
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pytestmark = pytest.mark.timeout(10)
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import xgboost as xgb
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from xgboost import testing
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pytestmark = testing.timeout(10)
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class TestOMP:
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def test_omp(self):
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@ -9,6 +9,7 @@ import pytest
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import testing as tm
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import xgboost as xgb
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from xgboost import testing
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if tm.no_spark()["condition"]:
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pytest.skip(msg=tm.no_spark()["reason"], allow_module_level=True)
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@ -37,7 +38,7 @@ from .utils import SparkTestCase
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logging.getLogger("py4j").setLevel(logging.INFO)
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pytestmark = pytest.mark.timeout(60)
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pytestmark = testing.timeout(60)
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class XgboostLocalTest(SparkTestCase):
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@ -29,6 +29,7 @@ from test_with_sklearn import run_data_initialization, run_feature_weights
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from xgboost.data import _is_cudf_df
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import xgboost as xgb
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from xgboost import testing
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if sys.platform.startswith("win"):
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pytest.skip("Skipping dask tests on Windows", allow_module_level=True)
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@ -44,7 +45,7 @@ from xgboost.dask import DaskDMatrix
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dask.config.set({"distributed.scheduler.allowed-failures": False})
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pytestmark = pytest.mark.timeout(30)
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pytestmark = testing.timeout(30)
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if hasattr(HealthCheck, 'function_scoped_fixture'):
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suppress = [HealthCheck.function_scoped_fixture]
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@ -1,20 +1,20 @@
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from typing import Callable, Optional
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import collections
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import importlib.util
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import numpy as np
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import xgboost as xgb
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import testing as tm
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import tempfile
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import os
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import shutil
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import pytest
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import json
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import os
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import tempfile
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from typing import Callable, Optional
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import numpy as np
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import pytest
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import testing as tm
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from sklearn.utils.estimator_checks import parametrize_with_checks
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import xgboost as xgb
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from xgboost import testing
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rng = np.random.RandomState(1994)
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pytestmark = [pytest.mark.skipif(**tm.no_sklearn()), pytest.mark.timeout(30)]
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from sklearn.utils.estimator_checks import parametrize_with_checks
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pytestmark = [pytest.mark.skipif(**tm.no_sklearn()), testing.timeout(30)]
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def test_binary_classification():
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