code: def test_stacked_split(self):
      if (
          Stack in self.unsupported_blocks
          or Split in self.unsupported_blocks
      ):
          self.skipTest(
              "Stack or Split not supported by adapter config."
          )
  
      model = self.build_model()
      # split into two stacks
      model.set_active_adapters(
          Split(Stack("a", "b"), Stack("c", "d"), splits=64)
      )
  
      self.training_pass(model)
  
imports: import unittest
  import torch
  import adapters
  from adapters import IA3Config, LoRAConfig, PrefixTuningConfig, SeqBnConfig
  from adapters.composition import Average, BatchSplit, Fuse, Parallel, Split, Stack, parse_composition
  from tests.test_adapter import ids_tensor
  from transformers import BertConfig, BertForSequenceClassification
  from transformers.testing_utils import require_torch, torch_device
label_desc: Use image node_id 7 for calling the AdapterCompositionTest obj's underlying member method code with example usage: obj.test_stacked_split() without return types