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.
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code: def initialize(self, ctx):
      """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.
      """
      self.manifest = ctx.manifest
      properties = ctx.system_properties
      model_dir = properties.get("model_dir")
  
      self.device = torch.device(
          "cuda:" + str(properties.get("gpu_id"))
          if torch.cuda.is_available()
          and properties.get("gpu_id") is not None
          else "cpu"
      )
      # Loading the model and tokenizer from checkpoint and config files based on the user's choice of mode
      # further setup config can be added.
      with zipfile.ZipFile(model_dir + "/model.zip", "r") as zip_ref:
          zip_ref.extractall(model_dir + "/model")
  
      self.pipe = DiffusionPipeline.from_pretrained(
          model_dir + "/model"
      )
      self.pipe.to(self.device)
      logger.info(
          "Diffusion model from path %s loaded successfully", model_dir
      )
  
      self.initialized = True
  
file_path: serve/examples/diffusers/stable_diffusion_handler.py
imports: import logging
  import zipfile
  from abc import ABC
  import diffusers
  import numpy
  import torch
  from diffusers import DiffusionPipeline
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 2 for calling the DiffusersHandler obj's underlying member method code with example usage: obj.initialize(ctx) without return types