Method config_spec

lit_nlp/components/shap_explainer.py:94–106

(self)

    return is_tabular and has_outputs

  def config_spec(self) -> types.Spec:
    return {
        EXPLAIN_KEY: types.SingleFieldMatcher(
            spec='output',
            types=[
                'MulticlassPreds',
                'RegressionScore',
                'Scalar',
                'SparseMultilabelPreds',
            ],
        ),
        SAMPLE_KEY: types.Scalar(min_val=0, max_val=50, default=30, step=1),
    }

  def meta_spec(self) -> types.Spec:
    return {'saliency': types.FeatureSalience(autorun=False, signed=True)}