[Python] I get multi-class error when trying to use roc_auc_score from scikit-learn even...

Even if I put the multi class argument, the next error is about the dimension:

numpy.exceptions.AxisError: axis 1 is out of bounds for array of dimension 1


This is the original run:

Number of gates for each filter: 784
1591it [00:15, 102.42it/s]
ACC TRAIN 0 valid 0.5849989190888902
RMSE: 0
[0 2 1 ... 2 0 1]
[ 0.77736357 0.3725196 1.01126466 ... 0.26738772 -0.063023
0.77434902]
The y_label is 1D.
The pred_proba is 1D.
Traceback (most recent call last):
File "C:\Users\user\Desktop\Fairness\infer_truth_tables.py", line 359, in <module>
print("ROC (%)", 100 * roc_auc_score(y_label, pred_proba)) #y_true, #y_score
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\user\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\sklearn\utils\_param_validation.py", line 211, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\user\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\sklearn\metrics\_ranking.py", line 619, in roc_auc_score
raise ValueError("multi_class must be in ('ovo', 'ovr')")
ValueError: multi_class must be in ('ovo', 'ovr')


I am using scikit-learn v1.3 (latest).

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