parameters: (self, name="entropy")
docstring: The entropy of Normal distribution(s).
  
      Args:
        name: The name to give this op.
  
      Returns:
        entropy: tensor of dtype `dtype`, the entropy.
docstring_summary: The entropy of Normal distribution(s).
docstring_tokens: The entropy of Normal distribution ( s ) .
function: def entropy(self, name="entropy"):
      """The entropy of Normal distribution(s).
  
      Args:
        name: The name to give this op.
  
      Returns:
        entropy: tensor of dtype `dtype`, the entropy.
      """
      with ops.name_scope(self.name):
        with ops.op_scope([self._mu, self._sigma], name):
          two_pi_e1 = constant_op.constant(
              2 * math.pi * math.exp(1), dtype=self.dtype)
          # Use broadcasting rules to calculate the full broadcast sigma.
          sigma = self._sigma * array_ops.ones_like(self._mu)
          return 0.5 * math_ops.log(two_pi_e1 * math_ops.square(sigma))
function_tokens: def entropy ( self , name = "entropy" ) : with ops . name_scope ( self . name ) : with ops . op_scope ( [ self . _mu , self . _sigma ] , name ) : two_pi_e1 = constant_op . constant ( 2 * math . pi * math . exp ( 1 ) , dtype = self . dtype ) # Use broadcasting rules to calculate the full broadcast sigma. sigma = self . _sigma * array_ops . ones_like ( self . _mu ) return 0.5 * math_ops . log ( two_pi_e1 * math_ops . square ( sigma ) )