code: def test_build_layer_specific_params_additional_module(self):
      model = AutoModelForSequenceClassification.from_pretrained(
          "sshleifer/tiny-distilroberta-base"
      )
      # This additional module is not even used by forward() but it triggers the check that prevents
      #  this unknown setting from being used together with the layer-specific fine-tuning functionality.
      model.additional_unused_module = nn.Linear(
          model.config.hidden_size, model.config.num_labels
      )
  
      base_lr = 2e-5
      fine_tuning_arguments = FineTuningArguments(base_lr, 0.95)
  
      with self.assertRaisesRegex(
          ValueError, "Fine-tuning arguments are not supported"
      ):
          _build_layer_specific_params(
              model, base_lr, fine_tuning_arguments
          )
  
file_path: small-text/tests/unit/small_text/integrations/transformers/utils/test_classification.py
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import patch, MagicMock
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
label_desc: Use image node_id 4 for calling the BuildLayerSpecificParamsTest obj's underlying member method code with example usage: obj.test_build_layer_specific_params_additional_module() without return types