code: def test_stable_diffusion_no_safety_checker(self):
      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,
      )
      assert isinstance(pipe, OnnxStableDiffusionPipeline)
      assert pipe.safety_checker is None
  
      image = pipe("example prompt", num_inference_steps=2).images[0]
      assert image is not None
  
      # check that there's no error when saving a pipeline with one of the models being None
      with tempfile.TemporaryDirectory() as tmpdirname:
          pipe.save_pretrained(tmpdirname)
          pipe = OnnxStableDiffusionPipeline.from_pretrained(tmpdirname)
  
      # sanity check that the pipeline still works
      assert pipe.safety_checker is None
      image = pipe("example prompt", num_inference_steps=2).images[0]
      assert image is not None
  
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 7 for calling the OnnxStableDiffusionPipelineIntegrationTests obj's underlying member method code with example usage: obj.test_stable_diffusion_no_safety_checker() without return types