code: def test_asr_forward_linear_pre(self, model, name):
      model.eval()
      torch.random.manual_seed(0)
      input_signal = torch.randn(2, 512)
      input_signal_length = torch.tensor([512, 512], dtype=torch.int32)
  
      origial_output = model(
          input_signal=input_signal,
          input_signal_length=input_signal_length,
      )[0]
  
      model.add_adapter(name=name, cfg=get_adapter_cfg())
      new_output = model(
          input_signal=input_signal,
          input_signal_length=input_signal_length,
      )[0]
  
      assert torch.mean(torch.abs(origial_output - new_output)) < 1e-5
  
imports: import pytest
  import torch
  from omegaconf import DictConfig, ListConfig, OmegaConf
  from nemo.collections.asr.models import ASRModel, EncDecCTCModel, EncDecRNNTModel
  from nemo.collections.asr.parts.submodules.adapters import multi_head_attention_adapter_module
  from nemo.collections.asr.parts.utils import adapter_utils
  from nemo.collections.common.parts import adapter_modules
  from nemo.core.classes.mixins.access_mixins import AccessMixin
  from nemo.core.classes.mixins.adapter_mixins import AdapterModuleMixin, get_registered_adapter
  from nemo.core.utils import numba_utils
  from nemo.core.utils.numba_utils import __NUMBA_MINIMUM_VERSION__
  from nemo.utils import config_utils, model_utils
label_desc: Use image node_id 11 for calling the TestASRAdapterMixin obj's underlying member method code with example usage: obj.test_asr_forward_linear_pre(model, name) without return types