code: def pointmass_q(shape, name=None):
      with tf.variable_scope(name, default_name="pointmass_q"):
          min_mean = 1e-3
          mean = tf.get_variable("mean", shape)
          rv = PointMass(tf.maximum(tf.nn.softplus(mean), min_mean))
          return rv
  
file_path: edward/examples/deep_exponential_family.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import numpy
  import os
  import tensorflow
  from datetime import datetime
  from edward.models import Gamma, Poisson, Normal, PointMass, TransformedDistribution
  from edward.util import Progbar
  from observations import nips
label_desc: Use image node_id 1 for calling a global function with example usage: pointmass_q(shape, name) and returns: rv