code: def test_batch_split_equivalent(self):
      if BatchSplit in self.unsupported_blocks:
          self.skipTest("BatchSplit not supported by adapter config.")
  
      model = self.build_model()
      model.set_active_adapters("a")
      model.eval()
      input_ids = ids_tensor((2, 128), 1000)
      output_a = model(input_ids[:1])
  
      model.set_active_adapters("b")
      output_b = model(input_ids[1:2])
  
      model.set_active_adapters(
          BatchSplit("a", "b", batch_sizes=[1, 1])
      )
      output = model(input_ids)
  
      self.assertTrue(
          torch.allclose(output_a[0], output[0][0], atol=1e-6)
      )
      self.assertTrue(
          torch.allclose(output_b[0], output[0][1], atol=1e-6)
      )
  
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 18 for calling the AdapterCompositionTest obj's underlying member method code with example usage: obj.test_batch_split_equivalent() without return types