docstr: Returns an iterator over module variational strategies, yielding both
  the name of the variational strategy as well as the strategy itself.
  
  Yields:
      (string, VariationalStrategy): Tuple containing the name of the
          strategy and the strategy
code: def named_added_loss_terms(self):
      """Returns an iterator over module variational strategies, yielding both
      the name of the variational strategy as well as the strategy itself.
  
      Yields:
          (string, VariationalStrategy): Tuple containing the name of the
              strategy and the strategy
  
      """
      return _extract_named_added_loss_terms(
          module=self, memo=None, prefix=""
      )
  
imports: import copy
  import inspect
  import itertools
  import operator
  from collections import OrderedDict
  from typing import Union
  import torch
  from linear_operator.operators import LinearOperator
  from torch import nn, Tensor
  from torch.distributions import Distribution
  from .constraints import Interval
label_desc: Use image node_id 11 for calling the Module obj's underlying member method code with example usage: obj.named_added_loss_terms() and returns: _extract_named_added_loss_terms