class_docstr: set config of preprocess, postprocess and visualize
  Args:
      model_dir (str): root path of infer_cfg.yml
class_docstr_tok: ["set","config","of","preprocess",",","postprocess","and","visualize","Args",":","model_dir","(","str",")",":","root","path","of","infer_cfg.yml"]
docstr: Raises:
      ValueError: loaded model not in supported model type
docstr_tok: ["Raises",":","ValueError",":","loaded","model","not","in","supported","model","type"]
code: def check_model(self, yml_conf):
      """
      Raises:
          ValueError: loaded model not in supported model type
      """
      for support_model in SUPPORT_MODELS:
          if support_model in yml_conf["arch"]:
              return True
      raise ValueError(
          "Unsupported arch: {}, expect {}".format(
              yml_conf["arch"], SUPPORT_MODELS
          )
      )
  
imports: import copy
  from paddle_serving_server.web_service import WebService, Op
  from paddle_serving_server.proto import general_model_config_pb2
  import google.protobuf.text_format
  import os
  import numpy
  import base64
  from PIL import Image
  import io
  from preprocess_ops import Compose
  from postprocess_ops import HRNetPostProcess
  from argparse import ArgumentParser, RawDescriptionHelpFormatter
  import yaml
label_desc: Use image node_id 2 for calling the PredictConfig obj's underlying member method code with example usage: obj.check_model(yml_conf) and returns: True