a94dbd2936fdc64e921333c04e0d66d491efc706,src/spn/algorithms/stats/Moments.py,,Moment,#,29

Before Change

    if evidence_scope is None:
        evidence_scope = set()

    assert not (len(evidence_scope) > 0 and evidence is None)

    assert len(feature_scope.intersection(evidence_scope)) == 0

    marg_spn = marginalize(spn, keep=feature_scope | evidence_scope)

After Change

    node_moments = {Sum: sum_moment, Product: prod_moment}

    for node in node_moment.keys():
        try:
            moment = node_moment[node]
            node_ll = node_likelihoods[node]
        except KeyError:
            raise AssertionError("Node type {} doe not have associated moment and likelihoods".format(node))
        node_moments[key] = leaf_moment(moment, node_ll)

    if evidence is None:
        // fake_evidence needs to be computed
        evidence = np.full((1, len(spn.scope)), np.nan)

Instances