def log_posterior(x, t):
        mu, log_sigma = x[:, 0], x[:, 1]
        prior       = norm.logpdf(log_sigma, 0, 1.35)
        likelihood  = norm.logpdf(mu,        0, np.exp(log_sigma))
        return prior + likelihood

    # Build variational objective.
An example 2D intractable distribution:
dataset/ETHPy150Open HIPS/autograd/examples/black_box_svi.py/log_posterior