code: def sample(self, prior, num_samples):
      max_loglike = self.max_loglike
      samples = np.empty((0, self.x_dim))
      while samples.shape[0] < num_samples:
          x = prior.sample(num_samples)
          loglike = self(x)
          ratio = np.exp(loglike - max_loglike)
          r = np.random.uniform(low=0, high=1, size=(num_samples,))
          samples = np.vstack((x[np.where(ratio > r)], samples))
      return samples[0:num_samples]
  
imports: import copy
  import numpy
  from scipy.stats import multivariate_normal
  import scipy.special
label_desc: Use image node_id 4 for calling the Likelihood obj's underlying member method code with example usage: obj.sample(prior, num_samples) and returns: samples