Use config_context in sklearn interface. (#8141)
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@@ -1,13 +1,15 @@
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# -*- coding: utf-8 -*-
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import xgboost as xgb
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import multiprocessing
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from concurrent.futures import ThreadPoolExecutor
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import pytest
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import testing as tm
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import xgboost as xgb
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@pytest.mark.parametrize('verbosity_level', [0, 1, 2, 3])
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@pytest.mark.parametrize("verbosity_level", [0, 1, 2, 3])
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def test_global_config_verbosity(verbosity_level):
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def get_current_verbosity():
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return xgb.get_config()['verbosity']
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return xgb.get_config()["verbosity"]
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old_verbosity = get_current_verbosity()
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with xgb.config_context(verbosity=verbosity_level):
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@@ -16,13 +18,48 @@ def test_global_config_verbosity(verbosity_level):
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assert old_verbosity == get_current_verbosity()
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@pytest.mark.parametrize('use_rmm', [False, True])
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@pytest.mark.parametrize("use_rmm", [False, True])
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def test_global_config_use_rmm(use_rmm):
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def get_current_use_rmm_flag():
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return xgb.get_config()['use_rmm']
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return xgb.get_config()["use_rmm"]
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old_use_rmm_flag = get_current_use_rmm_flag()
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with xgb.config_context(use_rmm=use_rmm):
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new_use_rmm_flag = get_current_use_rmm_flag()
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assert new_use_rmm_flag == use_rmm
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assert old_use_rmm_flag == get_current_use_rmm_flag()
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def test_nested_config():
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with xgb.config_context(verbosity=3):
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assert xgb.get_config()["verbosity"] == 3
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with xgb.config_context(verbosity=2):
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assert xgb.get_config()["verbosity"] == 2
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with xgb.config_context(verbosity=1):
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assert xgb.get_config()["verbosity"] == 1
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assert xgb.get_config()["verbosity"] == 2
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assert xgb.get_config()["verbosity"] == 3
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with xgb.config_context(verbosity=3):
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assert xgb.get_config()["verbosity"] == 3
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with xgb.config_context(verbosity=None):
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assert xgb.get_config()["verbosity"] == 3 # None has no effect
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verbosity = xgb.get_config()["verbosity"]
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xgb.set_config(verbosity=2)
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assert xgb.get_config()["verbosity"] == 2
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with xgb.config_context(verbosity=3):
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assert xgb.get_config()["verbosity"] == 3
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xgb.set_config(verbosity=verbosity) # reset
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def test_thread_safty():
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n_threads = multiprocessing.cpu_count()
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futures = []
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with ThreadPoolExecutor(max_workers=n_threads) as executor:
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for i in range(256):
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f = executor.submit(test_nested_config)
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futures.append(f)
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for f in futures:
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f.result()
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