class_docstr: A class object for the data handling activities of Image Classification
  Task and returns a KServe compatible response.
  
  Args:
      kserve (class object): The Model class from the KServe
      modeule is passed here.
docstr: Initialize the model name, predictor host and the explainer host
  
  Args:
      name (str): Name of the model.
      predictor_host (str): The host in which the predictor runs.
docstr_tok: ["Initialize","the","model","name",",","predictor","host","and","the","explainer","host","Args",":","name","(","str",")",":","Name","of","the","model",".","predictor_host","(","str",")",":","The","host","in","which","the","predictor","runs","."]
code: def __init__(self, name: str, predictor_host: str):
      """Initialize the model name, predictor host and the explainer host
  
      Args:
          name (str): Name of the model.
          predictor_host (str): The host in which the predictor runs.
      """
      super().__init__(name)
      self.predictor_host = predictor_host
      self.explainer_host = predictor_host
      logging.info("MODEL NAME %s", name)
      logging.info("PREDICTOR URL %s", self.predictor_host)
      logging.info("EXPLAINER URL %s", self.explainer_host)
      self.timeout = 100
  
file_path: serve/kubernetes/kserve/image_transformer/image_transformer/image_transformer.py
imports: import base64
  import io
  import json
  import logging
  from typing import Dict, List
  import kserve
  import torchvision.transforms
  import tornado
  from kserve.model import Model
  from PIL import Image
label_desc: Use image node_id 1 to create a new ImageTransformer object from inherited base classes: Model with example: obj = ImageTransformer(name, predictor_host)