code: def inverse_gamma_log_prob(self, val):
      conc = self.parameters["concentration"]
      rate = self.parameters["rate"]
      result = -(conc + 1) * tf.log(val)
      result -= rate * tf.reciprocal(val)
      result += -tf.lgamma(conc) + conc * tf.log(rate)
      return result
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from edward.models.random_variables import *
label_desc: Use image node_id 10 for calling a global function with example usage: inverse_gamma_log_prob(val) and returns: result