code: def pipeline_process(
      model_dir=None,
      optization_methods=None,
      scheduler=None,
      seed=-1,
      *args,
  ):
      if runner_process.pool is None:
          runner_process.pool = runner_process.RunnerPool()
      if runner_process.var_dict is None:
          runner_process.var_dict = multiprocessing.Manager().dict()
      runner_process.pool.apply(
          pipeline,
          args=(
              model_dir,
              runner_process.var_dict,
              optization_methods,
              scheduler,
              seed,
              *args,
          ),
      )
      return (
          runner_process.var_dict["image"],
          runner_process.var_dict["time"],
      )
  
file_path: BigDL/python/nano/client-application/StableDiffusion/launch.py
imports: import gradio
  import os
  import multiprocessing
  import time
  import psutil
  from stable_diffusion.runner import StableDiffusionRunner
  from stable_diffusion.converter import convert
  from stable_diffusion.pipelines import NanoStableDiffusionPipeline
  from stable_diffusion.utils import get_snapshot_dir_from_model_version
  from stable_diffusion import runner_process
  import click
label_desc: Use image node_id 3 for calling a global function with example usage: pipeline_process(model_dir, optization_methods, scheduler, seed) and returns: runner_process,  runner_process