class_docstr: Diffusers handler class for text to image generation.
docstr: In this initialize function, the Stable Diffusion model is loaded and
  initialized here.
  Args:
      ctx (context): It is a JSON Object containing information
      pertaining to the model artifacts parameters.
docstr_tok: ["In","this","initialize","function",",","the","Stable","Diffusion","model","is","loaded","and","initialized","here",".","Args",":","ctx","(","context",")",":","It","is","a","JSON","Object","containing","information","pertaining","to","the","model","artifacts","parameters","."]
code: def initialize(self, ctx: Context):
      """In this initialize function, the Stable Diffusion model is loaded and
      initialized here.
      Args:
          ctx (context): It is a JSON Object containing information
          pertaining to the model artifacts parameters.
      """
      model_dir = ctx.system_properties.get("model_dir")
      model_name = ctx.model_yaml_config["handler"]["model_name"]
      model_path = ctx.model_yaml_config["handler"]["model_path"]
      self.max_new_tokens = int(
          ctx.model_yaml_config["handler"]["max_new_tokens"]
      )
  
      model_config = {
          "tensor_parallel": int(
              ctx.model_yaml_config["handler"]["tensor_parallel"]
          ),
          "max_length": int(
              ctx.model_yaml_config["handler"]["max_length"]
          ),
      }
      self.pipe = mii.pipeline(
          model_name_or_path=model_path,
          model_config=model_config,
      )
      logger.info("Model %s loaded successfully", model_name)
      self.initialized = True
  
file_path: serve/examples/large_models/deepspeed_mii/LLM/DeepSpeed_mii_handler.py
imports: import logging
  import os
  from abc import ABC
  import mii
  from ts.context import Context
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 2 for calling the DeepSpeedMIIHandler obj's underlying member method code with example usage: obj.initialize(ctx) without return types