code: def add_deeplab_config(cfg):
      """
      Add config for DeepLab.
      """
      # We retry random cropping until no single category in semantic segmentation GT occupies more
      # than `SINGLE_CATEGORY_MAX_AREA` part of the crop.
      cfg.INPUT.CROP.SINGLE_CATEGORY_MAX_AREA = 1.0
      # Used for `poly` learning rate schedule.
      cfg.SOLVER.POLY_LR_POWER = 0.9
      cfg.SOLVER.POLY_LR_CONSTANT_ENDING = 0.0
      # Loss type, choose from `cross_entropy`, `hard_pixel_mining`.
      cfg.MODEL.SEM_SEG_HEAD.LOSS_TYPE = "hard_pixel_mining"
      # DeepLab settings
      cfg.MODEL.SEM_SEG_HEAD.PROJECT_FEATURES = ["res2"]
      cfg.MODEL.SEM_SEG_HEAD.PROJECT_CHANNELS = [48]
      cfg.MODEL.SEM_SEG_HEAD.ASPP_CHANNELS = 256
      cfg.MODEL.SEM_SEG_HEAD.ASPP_DILATIONS = [6, 12, 18]
      cfg.MODEL.SEM_SEG_HEAD.ASPP_DROPOUT = 0.1
      cfg.MODEL.SEM_SEG_HEAD.USE_DEPTHWISE_SEPARABLE_CONV = False
      # Backbone new configs
      cfg.MODEL.RESNETS.RES4_DILATION = 1
      cfg.MODEL.RESNETS.RES5_MULTI_GRID = [1, 2, 4]
      # ResNet stem type from: `basic`, `deeplab`
      cfg.MODEL.RESNETS.STEM_TYPE = "deeplab"
  
label_desc: Use image node_id 1 for calling a global function with example usage: add_deeplab_config(cfg) without return types