Description
Describe the bug
When running check_estimator on an estimator with binary_only tag set to true the check_sparsify_coefficients test uses inputs with more than 2 classes.
Steps/Code to Reproduce
import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.utils.estimator_checks import check_estimator
from sklearn.utils.validation import check_array
class TestCheckSparsifyCoefBinary(LogisticRegression):
def fit(self, X, y, sample_weight=None):
num_classes = len(np.unique(check_array(y, ensure_2d=False)))
if num_classes > 2:
raise Exception(f"Found {num_classes} classes in binary estimator")
return super().fit(X=X, y=y, sample_weight=sample_weight)
def _more_tags(self):
return dict(binary_only=True)
check_estimator(TestCheckSparsifyCoefBinary)Expected Results
all checks pass
Actual Results
Traceback (most recent call last):
File "test.py", line 33, in <module>
check_estimator(TestCheckSparsifyBinary)
File "/home/scgraham/repos/scikit-learn/sklearn/utils/estimator_checks.py", line 466, in check_estimator
check(estimator)
File "/home/scgraham/repos/scikit-learn/sklearn/utils/_testing.py", line 317, in wrapper
return fn(*args, **kwargs)
File "/home/scgraham/repos/scikit-learn/sklearn/utils/estimator_checks.py", line 2481, in check_sparsify_coefficients
est.fit(X, y)
File "test.py", line 12, in fit
raise Exception(f"Found {num_classes} classes in binary estimator")
Exception: Found 3 classes in binary estimatorVersions
System:
python: 3.8.2 (default, Mar 26 2020, 15:53:00) [GCC 7.3.0]
executable: /home/scgraham/miniconda3/envs/sklearn/bin/python
machine: Linux-4.4.0-18362-Microsoft-x86_64-with-glibc2.10
Python dependencies:
pip: 20.0.2
setuptools: 46.1.1.post20200323
sklearn: 0.23.dev0
numpy: 1.18.1
scipy: 1.4.1
Cython: 0.29.15
pandas: 1.0.3
matplotlib: None
joblib: 0.14.1
Built with OpenMP: True