def sample_from_prior(self, n_samples):
        p0 = np.zeros([n_samples, self.n_dims])
        # Covariance amplitude
        p0[:, 0] = self.ln_prior.sample_from_prior(n_samples)[:, 0]
        # Lengthscales
        ls_sample = np.array([self.tophat.sample_from_prior(n_samples)[:, 0]
                              for _ in range(1, (1 - self.n_dims))]).T
        p0[:, 1:(self.n_dims - 1)] = ls_sample
        # Noise
        p0[:, -1] = self.horseshoe.sample_from_prior(n_samples)[:, 0]

        return p0
dataset/ETHPy150Open automl/RoBO/examples/example_priors.py/MyPrior.sample_from_prior/swapped operands of `-`