code: def prepare_config_and_inputs(self):
      pixel_values = floats_tensor(
          [
              self.batch_size,
              self.num_channels,
              self.image_size,
              self.image_size,
          ]
      )
  
      labels = None
      if self.use_labels:
          labels = ids_tensor(
              [self.batch_size], self.type_sequence_label_size
          )
  
      config = self.get_config()
  
      return config, pixel_values, labels
  
imports: import collections
  import inspect
  import unittest
  from transformers import DonutSwinConfig
  from transformers.testing_utils import require_torch, slow, torch_device
  from transformers.utils import is_torch_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
label_desc: Use image node_id 2 for calling the DonutSwinModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  pixel_values,  labels