aae4f34978f5672448990d1f029b72d31e09a215,gpflow/likelihoods.py,MultiClass,variational_expectations,#MultiClass#Any#Any#Any#,427

Before Change

        if isinstance(self.invlink, RobustMax):
            gh_x, gh_w = hermgauss(self.num_gauss_hermite_points)
            p = self.invlink.prob_is_largest(Y, Fmu, Fvar, gh_x, gh_w)
            return p * np.log(1 - self.invlink.epsilon) + (1. - p) * np.log(self.invlink._eps_K1)
        else:
            raise NotImplementedError

    def predict_mean_and_var(self, Fmu, Fvar):

After Change

    def variational_expectations(self, Fmu, Fvar, Y):
        if isinstance(self.invlink, RobustMax):
            with params_as_tensors_for(self.invlink):
                gh_x, gh_w = hermgauss(self.num_gauss_hermite_points)
                p = self.invlink.prob_is_largest(Y, Fmu, Fvar, gh_x, gh_w)
                ve = p * tf.log(1. - self.invlink.epsilon) + (1. - p) * tf.log(self.invlink._eps_K1)
            return ve
        else:
            raise NotImplementedError

Instances