Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Assert matching length of evaluation inputs. #5540

Merged
merged 1 commit into from
Apr 17, 2020
Merged

Assert matching length of evaluation inputs. #5540

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 4 additions & 0 deletions python-package/xgboost/sklearn.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -510,6 +510,8 @@ def fit(self, X, y, sample_weight=None, base_margin=None,
raise TypeError('Unexpected input type for `eval_set`')
if sample_weight_eval_set is None:
sample_weight_eval_set = [None] * len(eval_set)
else:
assert len(eval_set) == len(sample_weight_eval_set)
evals = list(
DMatrix(eval_set[i][0], label=eval_set[i][1], missing=self.missing,
weight=sample_weight_eval_set[i], nthread=self.n_jobs)
Expand Down Expand Up @@ -788,6 +790,8 @@ def fit(self, X, y, sample_weight=None, base_margin=None,
if eval_set is not None:
if sample_weight_eval_set is None:
sample_weight_eval_set = [None] * len(eval_set)
else:
assert len(sample_weight_eval_set) == len(eval_set)
evals = list(
DMatrix(eval_set[i][0],
label=self._le.transform(eval_set[i][1]),
Expand Down
11 changes: 11 additions & 0 deletions tests/python/test_with_sklearn.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -596,6 +596,17 @@ def test_validation_weights_xgbmodel():
assert all((logloss_with_weights[i] != logloss_without_weights[i]
for i in [0, 1]))

with pytest.raises(AssertionError):
# length of eval set and sample weight doesn't match.
clf.fit(X_train, y_train, sample_weight=weights_train,
eval_set=[(X_train, y_train), (X_test, y_test)],
sample_weight_eval_set=[weights_train])

with pytest.raises(AssertionError):
cls = xgb.XGBClassifier()
cls.fit(X_train, y_train, sample_weight=weights_train,
eval_set=[(X_train, y_train), (X_test, y_test)],
sample_weight_eval_set=[weights_train])

def test_validation_weights_xgbclassifier():
from sklearn.datasets import make_hastie_10_2
Expand Down