code: def run_ov(self, scheduler, version, precision, device, **kwargs):
      # set_env_var(OV_ENV_VAR)
      # calibration
      if self.need_init_pipeline(
          version, device, precision, "nano_openvino"
      ):
          self.pipe = NanoStableDiffusionPipeline.from_pretrained(
              pretrained_model_path=self.model_dir,
              accelerator="openvino",
              precision=precision,
              device=device,
          )
      self.init_scheduler(scheduler)
      with InferenceOptimizer.get_context(self.pipe.unet):
          image = self.pipe(**kwargs)[0]
      return image
  
imports: from typing import ClassVar, Optional
  import torch
  import os
  from bigdl.nano.pytorch import InferenceOptimizer
  from diffusers.schedulers import *
  from .utils import get_snapshot_dir_from_model_version
  from .pipelines import NanoStableDiffusionPipeline
label_desc: Use image node_id 12 for calling the StableDiffusionRunner obj's underlying member method code with example usage: obj.run_ov(scheduler, version, precision, device) and returns: image