code: def log_gaussian(params, scale):
      flat_params, _ = flatten(params)
      return np.sum(norm.logpdf(flat_params, 0, scale))
  
file_path: autograd/examples/neural_net_regression.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  import matplotlib.pyplot
  import autograd.numpy
  import autograd.numpy.random
  import autograd.scipy.stats.norm
  from autograd import grad
  from autograd.misc import flatten
  from autograd.misc.optimizers import adam
label_desc: Use image node_id 3 for calling a global function with example usage: log_gaussian(params, scale) and returns: np