parameters: (self, dist, mean_b, sd_b, mean=None, sd=None)
return_statement: return self._entropy(mean, sd) + self._kl_loss(dist, mean_b, sd_b, mean, sd)
docstring: r"""
          Evaluate cross entropy between normal distributions.
  
          Args:
              dist (str): Type of the distributions. Should be "Normal" in this case.
              mean_b (Tensor): Mean of distribution b.
              sd_b (Tensor): Standard deviation distribution b.
              mean_a (Tensor): Mean of distribution a. Default: self._mean_value.
              sd_a (Tensor): Standard deviation distribution a. Default: self._sd_value.
docstring_summary: r"""
          Evaluate cross entropy between normal distributions.
docstring_tokens: r Evaluate cross entropy between normal distributions .
function: def _cross_entropy(self, dist, mean_b, sd_b, mean=None, sd=None):
          r"""
          Evaluate cross entropy between normal distributions.
  
          Args:
              dist (str): Type of the distributions. Should be "Normal" in this case.
              mean_b (Tensor): Mean of distribution b.
              sd_b (Tensor): Standard deviation distribution b.
              mean_a (Tensor): Mean of distribution a. Default: self._mean_value.
              sd_a (Tensor): Standard deviation distribution a. Default: self._sd_value.
          """
          check_distribution_name(dist, 'Normal')
          return self._entropy(mean, sd) + self._kl_loss(dist, mean_b, sd_b, mean, sd)
function_tokens: def _cross_entropy ( self , dist , mean_b , sd_b , mean = None , sd = None ) : check_distribution_name ( dist , 'Normal' ) return self . _entropy ( mean , sd ) + self . _kl_loss ( dist , mean_b , sd_b , mean , sd )