code: def test_inference(self):
      device = "cpu"
  
      components = self.get_dummy_components()
      pipe = self.pipeline_class(**components)
      pipe.to(device)
      pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_dummy_inputs(device)
      image = pipe(**inputs).images
      image_slice = image[0, -3:, -3:, -1]
  
      self.assertEqual(image.shape, (1, 8, 8, 3))
      expected_slice = np.array(
          [
              0.6319,
              0.3526,
              0.3806,
              0.6327,
              0.4639,
              0.483,
              0.2583,
              0.5331,
              0.4852,
          ]
      )
      max_diff = np.abs(image_slice.flatten() - expected_slice).max()
      self.assertLessEqual(max_diff, 1e-3)
  
imports: import gc
  import tempfile
  import unittest
  import numpy
  import torch
  from transformers import AutoTokenizer, T5EncoderModel
  from diffusers import AutoencoderKL, DDIMScheduler, PixArtAlphaPipeline, Transformer2DModel
  from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineTesterMixin, to_np
label_desc: Use image node_id 5 for calling the PixArtAlphaPipelineFastTests obj's underlying member method code with example usage: obj.test_inference() without return types