parameters: (self, dist, concentration_b, rate_b, concentration_a=None, rate_a=None)
return_statement: return self._entropy(concentration_a, rate_a) +\
              self._kl_loss(dist, concentration_b, rate_b,
                            concentration_a, rate_a)
docstring: r"""
          Evaluate cross entropy between Gamma distributions.
  
          Args:
              dist (str): Type of the distributions. Should be "Gamma" in this case.
              concentration_b (Tensor): concentration of distribution b.
              rate_b (Tensor): rate of distribution b.
              concentration_a (Tensor): concentration of distribution a. Default: self._concentration.
              rate_a (Tensor): rate of distribution a. Default: self._rate.
docstring_summary: r"""
          Evaluate cross entropy between Gamma distributions.
docstring_tokens: r Evaluate cross entropy between Gamma distributions .
function: def _cross_entropy(self, dist, concentration_b, rate_b, concentration_a=None, rate_a=None):
          r"""
          Evaluate cross entropy between Gamma distributions.
  
          Args:
              dist (str): Type of the distributions. Should be "Gamma" in this case.
              concentration_b (Tensor): concentration of distribution b.
              rate_b (Tensor): rate of distribution b.
              concentration_a (Tensor): concentration of distribution a. Default: self._concentration.
              rate_a (Tensor): rate of distribution a. Default: self._rate.
          """
          check_distribution_name(dist, 'Gamma')
          return self._entropy(concentration_a, rate_a) +\
              self._kl_loss(dist, concentration_b, rate_b,
                            concentration_a, rate_a)
function_tokens: def _cross_entropy ( self , dist , concentration_b , rate_b , concentration_a = None , rate_a = None ) : check_distribution_name ( dist , 'Gamma' ) return self . _entropy ( concentration_a , rate_a ) + self . _kl_loss ( dist , concentration_b , rate_b , concentration_a , rate_a )