class_docstr: Diffusers handler class for text to image generation.
docstr: Generates the image relevant to the received text.
  Args:
      input_batch (list): List of Text from the pre-process function is passed here
  Returns:
      list : It returns a list of the generate images for the input text
docstr_tok: ["Generates","the","image","relevant","to","the","received","text",".","Args",":","input_batch","(","list",")",":","List","of","Text","from","the","pre-process","function","is","passed","here","Returns",":","list",":","It","returns","a","list","of","the","generate","images","for","the","input","text"]
code: def inference(self, inputs):
      """Generates the image relevant to the received text.
      Args:
          input_batch (list): List of Text from the pre-process function is passed here
      Returns:
          list : It returns a list of the generate images for the input text
      """
      inferences = self.pipe(
          inputs, max_new_tokens=self.max_new_tokens
      ).generated_texts
  
      logger.info("Generated text: %s", inferences)
      return inferences
  
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 4 for calling the DeepSpeedMIIHandler obj's underlying member method code with example usage: obj.inference(inputs) and returns: inferences