docs: def _compile_arithmetic_expression(self,
                                         expr: Expression,
                                         scope: Dict[str, TensorFluent],
                                         batch_size: Optional[int] = None,
                                         noise: Optional[List[tf.Tensor]] = None) -> TensorFluent:
          '''Compile an arithmetic expression `expr` into a TensorFluent
          in the given `scope` with optional batch size.
  
          Args:
              expr (:obj:`rddl2tf.expr.Expression`): A RDDL arithmetic expression.
              scope (Dict[str, :obj:`rddl2tf.fluent.TensorFluent`]): A fluent scope.
              batch_size (Optional[size]): The batch size.
  
          Returns:
              :obj:`rddl2tf.fluent.TensorFluent`: The compiled expression as a TensorFluent.
          '''
          etype = expr.etype
          args = expr.args
  
          if len(args) == 1:
              etype2op = {
                  '+': lambda x: x,
                  '-': lambda x: -x
              }
  
              if etype[1] not in etype2op:
                  raise ValueError('Invalid binary arithmetic expression:\n{}'.format(expr))
  
              op = etype2op[etype[1]]
              x = self._compile_expression(args[0], scope, batch_size, noise)
              fluent = op(x)
  
          else:
              etype2op = {
                  '+': lambda x, y: x + y,
                  '-': lambda x, y: x - y,
                  '*': lambda x, y: x * y,
                  '/': lambda x, y: x / y,
              }
  
              if etype[1] not in etype2op:
                  raise ValueError('Invalid binary arithmetic expression:\n{}'.format(expr))
  
              op = etype2op[etype[1]]
              x = self._compile_expression(args[0], scope, batch_size, noise)
              y = self._compile_expression(args[1], scope, batch_size, noise)
              fluent = op(x, y)
  
          return fluent