/usr/share/miniconda/envs/test/lib/python3.8/site-packages/responsibleai/rai_insights/rai_base_insights.py:87: in compute
    manager.compute()
/usr/share/miniconda/envs/test/lib/python3.8/site-packages/responsibleai_text/managers/explainer_manager.py:117: in compute
    self._explanation = explainer(eval_examples)
/usr/share/miniconda/envs/test/lib/python3.8/site-packages/shap/explainers/_partition.py:136: in __call__
    return super().__call__(
/usr/share/miniconda/envs/test/lib/python3.8/site-packages/shap/explainers/_explainer.py:266: in __call__
    row_result = self.explain_row(
/usr/share/miniconda/envs/test/lib/python3.8/site-packages/shap/explainers/_partition.py:154: in explain_row
    fm = MaskedModel(self.model, self.masker, self.link, self.linearize_link, *row_args)
/usr/share/miniconda/envs/test/lib/python3.8/site-packages/shap/utils/_masked_model.py:28: in __init__
    self._variants = ~self.masker.invariants(*args)
/usr/share/miniconda/envs/test/lib/python3.8/site-packages/shap/maskers/_text.py:297: in invariants
    invariants = np.zeros(len(self._tokenized_s), dtype=np.bool)
...
        if attr in __former_attrs__:
>           raise AttributeError(__former_attrs__[attr])
E           AttributeError: module 'numpy' has no attribute 'bool'.
E           `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
E           The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
E               https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations