code: def generate_from_prior(gen_params, num_samples, noise_dim, rs):
      latents = rs.randn(num_samples, noise_dim)
      return sigmoid(neural_net_predict(gen_params, latents))
  
imports: from __future__ import absolute_import, division
  from __future__ import print_function
  import autograd.numpy
  import autograd.numpy.random
  import autograd.scipy.stats.norm
  from autograd.scipy.special import expit
  from autograd import grad
  from autograd.misc.optimizers import adam
  from data import load_mnist, save_images
label_desc: Use image node_id 10 for calling a global function with example usage: generate_from_prior(gen_params, num_samples, noise_dim, rs) and returns: sigmoid