code: def _load_transforms(self, t_list):
      com = manager.TRANSFORMS
      transforms = []
      for t in t_list:
          ctype = t.pop("type")
          transforms.append(com[ctype](**t))
  
      return transforms
  
imports: import codecs
  import os
  import sys
  import time
  import yaml
  import numpy
  import cv2
  import paddle
  from paddle.inference import create_predictor, PrecisionType
  from paddle.inference import Config
  import paddleseg.transforms
  from paddleseg.core.infer import reverse_transform
  from paddleseg.cvlibs import manager
  from paddleseg.utils import TimeAverager
  from optic_flow_process import optic_flow_process
label_desc: Use image node_id 6 for calling the DeployConfig obj's underlying member method code with example usage: obj._load_transforms(t_list) and returns: transforms