code: def test_intermediate_state(self):
      number_of_steps = 0
  
      def test_callback_fn(
          step: int, timestep: int, latents: np.ndarray
      ) -> None:
          test_callback_fn.has_been_called = True
          nonlocal number_of_steps
          number_of_steps += 1
          if step == 0:
              assert latents.shape == (1, 4, 64, 64)
              latents_slice = latents[0, -3:, -3:, -1]
              expected_slice = np.array(
                  [
                      -0.6772,
                      -0.3835,
                      -1.2456,
                      0.1905,
                      -1.0974,
                      0.6967,
                      -1.9353,
                      0.0178,
                      1.0167,
                  ]
              )
  
              assert (
                  np.abs(latents_slice.flatten() - expected_slice).max()
                  < 1e-3
              )
          elif step == 5:
              assert latents.shape == (1, 4, 64, 64)
              latents_slice = latents[0, -3:, -3:, -1]
              expected_slice = np.array(
                  [
                      -0.3351,
                      0.2241,
                      -0.1837,
                      -0.2325,
                      -0.6577,
                      0.3393,
                      -0.0241,
                      0.5899,
                      1.3875,
                  ]
              )
  
              assert (
                  np.abs(latents_slice.flatten() - expected_slice).max()
                  < 1e-3
              )
  
      test_callback_fn.has_been_called = False
  
      pipe = OnnxStableDiffusionPipeline.from_pretrained(
          "runwayml/stable-diffusion-v1-5",
          revision="onnx",
          safety_checker=None,
          feature_extractor=None,
          provider=self.gpu_provider,
          sess_options=self.gpu_options,
      )
      pipe.set_progress_bar_config(disable=None)
  
      prompt = "Andromeda galaxy in a bottle"
  
      generator = np.random.RandomState(0)
      pipe(
          prompt=prompt,
          num_inference_steps=5,
          guidance_scale=7.5,
          generator=generator,
          callback=test_callback_fn,
          callback_steps=1,
      )
      assert test_callback_fn.has_been_called
      assert number_of_steps == 6
  
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 OnnxStableDiffusionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_intermediate_state() without return types