code: def test_pipeline_euler_ancestral(self):
      pipe = OnnxStableDiffusionPipeline.from_pretrained(
          self.hub_checkpoint, provider="CPUExecutionProvider"
      )
      pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(
          pipe.scheduler.config
      )
      pipe.set_progress_bar_config(disable=None)
  
      inputs = self.get_dummy_inputs()
      image = pipe(**inputs).images
      image_slice = image[0, -3:, -3:, -1]
  
      assert image.shape == (1, 128, 128, 3)
      expected_slice = np.array(
          [
              0.53817,
              0.60812,
              0.47384,
              0.49530,
              0.51894,
              0.49814,
              0.47984,
              0.38958,
              0.44271,
          ]
      )
  
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
  
imports: import tempfile
  import unittest
  import numpy
  from diffusers import DDIMScheduler, DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionPipeline, PNDMScheduler
  from diffusers.utils.testing_utils import is_onnx_available, nightly, require_onnxruntime, require_torch_gpu
  from ..test_pipelines_onnx_common import OnnxPipelineTesterMixin
label_desc: Use image node_id 6 for calling the OnnxStableDiffusionPipelineFastTests obj's underlying member method code with example usage: obj.test_pipeline_euler_ancestral() without return types