Feature selection with boruta python package

Question

I'm running this code

from boruta import BorutaPy

boruta_selector = BorutaPy(gbc, random_state=42)

boruta_selector.fit(X_train_v4.values, y_train_v4.values.ravel())

sel_X_train_v4 = boruta_selector.transform(X_train_v4.values)
sel_X_test_v4 = boruta_selector.transform(X_test_v4.values)

gbc.fit(sel_X_train_v4, y_train_v4)

boruta_preds = gbc.predict(sel_X_test_v4)

boruta_f1_score = round(f1_score(y_test_v4, boruta_preds, average='weighted'), 3)

I obtain the next error

--> 319             raise AttributeError(__former_attrs__[attr])
    320 
    321         if attr == 'testing':

AttributeError: module 'numpy' has no attribute 'int'.
`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations