code: def prepare_config_and_inputs(self):
      pixel_values = floats_tensor(
          [
              self.batch_size,
              self.num_channels,
              self.min_size,
              self.max_size,
          ]
      ).to(torch_device)
  
      task_inputs = (
          torch.randint(
              high=self.vocab_size,
              size=(self.batch_size, self.sequence_length),
          )
          .to(torch_device)
          .long()
      )
  
      pixel_mask = torch.ones(
          [self.batch_size, self.min_size, self.max_size],
          device=torch_device,
      )
  
      text_inputs = (
          torch.randint(
              high=self.vocab_size,
              size=(
                  self.batch_size,
                  self.num_queries - self.n_ctx,
                  self.sequence_length,
              ),
          )
          .to(torch_device)
          .long()
      )
  
      mask_labels = (
          torch.rand(
              [
                  self.batch_size,
                  self.num_labels,
                  self.min_size,
                  self.max_size,
              ],
              device=torch_device,
          )
          > 0.5
      ).float()
      class_labels = (
          torch.rand(
              (self.batch_size, self.num_labels), device=torch_device
          )
          > 0.5
      ).long()
  
      config = self.get_config()
      return (
          config,
          pixel_values,
          task_inputs,
          text_inputs,
          pixel_mask,
          mask_labels,
          class_labels,
      )
  
imports: import copy
  import inspect
  import unittest
  import numpy
  from tests.test_modeling_common import floats_tensor
  from transformers import OneFormerConfig, is_torch_available, is_vision_available
  from transformers.testing_utils import require_torch, require_torch_accelerator, require_torch_fp16, require_torch_multi_gpu, require_vision, slow, torch_device
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 2 for calling the OneFormerModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  pixel_values,  task_inputs,  text_inputs,  pixel_mask,  mask_labels,  class_labels