class_docstr: set config of preprocess, postprocess and visualize
  Args:
      infer_config (str): path of infer_cfg.yml
class_docstr_tok: ["set","config","of","preprocess",",","postprocess","and","visualize","Args",":","infer_config","(","str",")",":","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 time
  import numpy
  import pycuda.autoinit
  import pycuda.driver
  import tensorrt
  from collections import OrderedDict
  import os
  import yaml
  import json
  import glob
  import argparse
  from preprocess import Compose
  from preprocess import coco_clsid2catid
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