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.image_size, self.image_size],
              self.num_labels,
          )
  
      config = PoolFormerConfig(
          image_size=self.image_size,
          num_channels=self.num_channels,
          num_encoder_blocks=self.num_encoder_blocks,
          depths=self.depths,
          hidden_sizes=self.hidden_sizes,
          hidden_act=self.hidden_act,
          hidden_dropout_prob=self.hidden_dropout_prob,
          initializer_range=self.initializer_range,
      )
  
      return config, pixel_values, labels
  
imports: import inspect
  import unittest
  from transformers import is_torch_available, is_vision_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 2 for calling the PoolFormerModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  pixel_values,  labels