code: def build_model(self):
      model = BertForSequenceClassification(
          BertConfig(
              hidden_size=32,
              num_hidden_layers=4,
              num_attention_heads=4,
              intermediate_size=37,
          )
      )
      adapters.init(model)
      adapter_config = self.get_adapter_config()
      model.add_adapter("a", config=adapter_config)
      model.add_adapter("b", config=adapter_config)
      model.add_adapter("c", config=adapter_config)
      model.add_adapter("d", config=adapter_config)
      model.to(torch_device)
      model.train()
  
      return 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 2 for calling the AdapterCompositionTest obj's underlying member method code with example usage: obj.build_model() and returns: model