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Use pytest conventions consistently (#6337)

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* Do not derive from unittest.TestCase (not needed for pytest)

* assertRaises -> pytest.raises

* Simplify test_empty_dmatrix with test parametrization

* setUpClass -> setup_class, tearDownClass -> teardown_class

* Don't import unittest; import pytest

* Use plain assert

* Use parametrized tests in more places

* Fix test_gpu_with_sklearn.py

* Put back run_empty_dmatrix_reg / run_empty_dmatrix_cls

* Fix test_eta_decay_gpu_hist

* Add parametrized tests for monotone constraints

* Fix test names

* Remove test parametrization

* Revise test_slice to be not flaky
This commit is contained in:
Philip Hyunsu Cho
2020-11-19 17:00:15 -08:00
committed by GitHub
parent c763b50dd0
commit 9c9070aea2
34 changed files with 200 additions and 223 deletions
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64
tests/python/test_callback.py
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@@ -1,5 +1,4 @@
import xgboost as xgb
import unittest
import pytest
import os
import testing as tm
@@ -9,9 +8,9 @@ import tempfile
pytestmark = pytest.mark.skipif(**tm.no_sklearn())
class TestCallbacks(unittest.TestCase):
class TestCallbacks:
@classmethod
def setUpClass(cls):
def setup_class(cls):
from sklearn.datasets import load_breast_cancer
X, y = load_breast_cancer(return_X_y=True)
cls.X = X
@@ -148,9 +147,9 @@ class TestCallbacks(unittest.TestCase):
early_stop = xgb.callback.EarlyStopping(rounds=early_stopping_rounds,
save_best=True)
cls = xgb.XGBClassifier(booster='gblinear', n_estimators=10)
self.assertRaises(ValueError, lambda: cls.fit(X, y, eval_set=[(X, y)],
eval_metric=tm.eval_error_metric,
callbacks=[early_stop]))
with pytest.raises(ValueError):
cls.fit(X, y, eval_set=[(X, y)], eval_metric=tm.eval_error_metric,
callbacks=[early_stop])
# No error
early_stop = xgb.callback.EarlyStopping(rounds=early_stopping_rounds,
@@ -172,17 +171,20 @@ class TestCallbacks(unittest.TestCase):
watchlist = [(dtest, 'eval'), (dtrain, 'train')]
num_round = 4
warning_check = pytest.warns(UserWarning) if deprecated_callback else tm.noop_context()
# learning_rates as a list
# init eta with 0 to check whether learning_rates work
param = {'max_depth': 2, 'eta': 0, 'verbosity': 0,
'objective': 'binary:logistic', 'eval_metric': 'error',
'tree_method': tree_method}
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[scheduler([
0.8, 0.7, 0.6, 0.5
])],
evals_result=evals_result)
with warning_check:
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[scheduler([
0.8, 0.7, 0.6, 0.5
])],
evals_result=evals_result)
eval_errors_0 = list(map(float, evals_result['eval']['error']))
assert isinstance(bst, xgb.core.Booster)
# validation error should decrease, if eta > 0
@@ -193,10 +195,11 @@ class TestCallbacks(unittest.TestCase):
'objective': 'binary:logistic', 'eval_metric': 'error',
'tree_method': tree_method}
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[scheduler(
[0.8, 0.7, 0.6, 0.5])],
evals_result=evals_result)
with warning_check:
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[scheduler(
[0.8, 0.7, 0.6, 0.5])],
evals_result=evals_result)
eval_errors_1 = list(map(float, evals_result['eval']['error']))
assert isinstance(bst, xgb.core.Booster)
# validation error should decrease, if learning_rate > 0
@@ -208,11 +211,12 @@ class TestCallbacks(unittest.TestCase):
'eval_metric': 'error', 'tree_method': tree_method
}
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[scheduler(
[0, 0, 0, 0]
)],
evals_result=evals_result)
with warning_check:
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[scheduler(
[0, 0, 0, 0]
)],
evals_result=evals_result)
eval_errors_2 = list(map(float, evals_result['eval']['error']))
assert isinstance(bst, xgb.core.Booster)
# validation error should not decrease, if eta/learning_rate = 0
@@ -223,11 +227,12 @@ class TestCallbacks(unittest.TestCase):
return num_boost_round / (ithround + 1)
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[
scheduler(eta_decay)
],
evals_result=evals_result)
with warning_check:
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[
scheduler(eta_decay)
],
evals_result=evals_result)
eval_errors_3 = list(map(float, evals_result['eval']['error']))
assert isinstance(bst, xgb.core.Booster)
@@ -238,18 +243,15 @@ class TestCallbacks(unittest.TestCase):
assert eval_errors_3[i] != eval_errors_2[i]
def test_eta_decay_hist(self):
with pytest.warns(UserWarning):
self.run_eta_decay('hist', True)
self.run_eta_decay('hist', True)
self.run_eta_decay('hist', False)
def test_eta_decay_approx(self):
with pytest.warns(UserWarning):
self.run_eta_decay('approx', True)
self.run_eta_decay('approx', True)
self.run_eta_decay('approx', False)
def test_eta_decay_exact(self):
with pytest.warns(UserWarning):
self.run_eta_decay('exact', True)
self.run_eta_decay('exact', True)
self.run_eta_decay('exact', False)
def test_check_point(self):