code: def test_for_pretraining(self):
      config_and_inputs = self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_for_pretraining(
          *config_and_inputs
      )
  
imports: import os
  import tempfile
  import unittest
  from transformers import NezhaConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 10 for calling the NezhaModelTest obj's underlying member method code with example usage: obj.test_for_pretraining() without return types