docs: def _compile_expression(self,
                              expr: Expression,
                              scope: Dict[str, TensorFluent],
                              batch_size: Optional[int] = None,
                              noise: Optional[List[tf.Tensor]] = None) -> TensorFluent:
          '''Compile the expression `expr` into a TensorFluent
          in the given `scope` with optional batch size.
  
          Args:
              expr (:obj:`rddl2tf.expr.Expression`): A RDDL 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 TensorFluent.
          '''
          etype2compiler = {
              'constant':    self._compile_constant_expression,
              'pvar':        self._compile_pvariable_expression,
              'randomvar':   self._compile_random_variable_expression,
              'arithmetic':  self._compile_arithmetic_expression,
              'boolean':     self._compile_boolean_expression,
              'relational':  self._compile_relational_expression,
              'func':        self._compile_function_expression,
              'control':     self._compile_control_flow_expression,
              'aggregation': self._compile_aggregation_expression
          }
  
          etype = expr.etype
          if etype[0] not in etype2compiler:
              raise ValueError('Expression type unknown: {}'.format(etype))
  
          with self.graph.as_default():
              compiler_fn = etype2compiler[etype[0]]
              return compiler_fn(expr, scope, batch_size, noise)