def METHOD_NAME(self) -> None:
    """Test a problem with kl_div.
    """
    kK = 50
    kSeed = 10
    prng = np.random.RandomState(kSeed)
    # Generate a random reference distribution
    npSPriors = prng.uniform(0.0, 1.0, kK)
    npSPriors = npSPriors / sum(npSPriors)
    # Reference distribution
    p_refProb = cvx.Parameter(kK, nonneg=True)
    # Distribution to be estimated
    v_prob = cvx.Variable(kK)
    objkl = cvx.sum(cvx.kl_div(v_prob, p_refProb))
    constrs = [cvx.sum(v_prob) == 1]
    klprob = cvx.Problem(cvx.Minimize(objkl), constrs)
    p_refProb.value = npSPriors
    klprob.solve(solver=cvx.SCS, verbose=True)
    self.assertItemsAlmostEqual(v_prob.value, npSPriors, places=3)
    klprob.solve(solver=cvx.ECOS, verbose=True)
    self.assertItemsAlmostEqual(v_prob.value, npSPriors)