code: def add_panoptic_deeplab_config(cfg):
      """
      Add config for Panoptic-DeepLab.
      """
      # Reuse DeepLab config.
      add_deeplab_config(cfg)
      # Target generation parameters.
      cfg.INPUT.GAUSSIAN_SIGMA = 10
      cfg.INPUT.IGNORE_STUFF_IN_OFFSET = True
      cfg.INPUT.SMALL_INSTANCE_AREA = 4096
      cfg.INPUT.SMALL_INSTANCE_WEIGHT = 3
      cfg.INPUT.IGNORE_CROWD_IN_SEMANTIC = False
      # Optimizer type.
      cfg.SOLVER.OPTIMIZER = "ADAM"
      # Panoptic-DeepLab semantic segmentation head.
      # We add an extra convolution before predictor.
      cfg.MODEL.SEM_SEG_HEAD.HEAD_CHANNELS = 256
      cfg.MODEL.SEM_SEG_HEAD.LOSS_TOP_K = 0.2
      # Panoptic-DeepLab instance segmentation head.
      cfg.MODEL.INS_EMBED_HEAD = CN()
      cfg.MODEL.INS_EMBED_HEAD.NAME = "PanopticDeepLabInsEmbedHead"
      cfg.MODEL.INS_EMBED_HEAD.IN_FEATURES = ["res2", "res3", "res5"]
      cfg.MODEL.INS_EMBED_HEAD.PROJECT_FEATURES = ["res2", "res3"]
      cfg.MODEL.INS_EMBED_HEAD.PROJECT_CHANNELS = [32, 64]
      cfg.MODEL.INS_EMBED_HEAD.ASPP_CHANNELS = 256
      cfg.MODEL.INS_EMBED_HEAD.ASPP_DILATIONS = [6, 12, 18]
      cfg.MODEL.INS_EMBED_HEAD.ASPP_DROPOUT = 0.1
      # We add an extra convolution before predictor.
      cfg.MODEL.INS_EMBED_HEAD.HEAD_CHANNELS = 32
      cfg.MODEL.INS_EMBED_HEAD.CONVS_DIM = 128
      cfg.MODEL.INS_EMBED_HEAD.COMMON_STRIDE = 4
      cfg.MODEL.INS_EMBED_HEAD.NORM = "SyncBN"
      cfg.MODEL.INS_EMBED_HEAD.CENTER_LOSS_WEIGHT = 200.0
      cfg.MODEL.INS_EMBED_HEAD.OFFSET_LOSS_WEIGHT = 0.01
      # Panoptic-DeepLab post-processing setting.
      cfg.MODEL.PANOPTIC_DEEPLAB = CN()
      # Stuff area limit, ignore stuff region below this number.
      cfg.MODEL.PANOPTIC_DEEPLAB.STUFF_AREA = 2048
      cfg.MODEL.PANOPTIC_DEEPLAB.CENTER_THRESHOLD = 0.1
      cfg.MODEL.PANOPTIC_DEEPLAB.NMS_KERNEL = 7
      cfg.MODEL.PANOPTIC_DEEPLAB.TOP_K_INSTANCE = 200
      # If set to False, Panoptic-DeepLab will not evaluate instance segmentation.
      cfg.MODEL.PANOPTIC_DEEPLAB.PREDICT_INSTANCES = True
      cfg.MODEL.PANOPTIC_DEEPLAB.USE_DEPTHWISE_SEPARABLE_CONV = False
      # This is the padding parameter for images with various sizes. ASPP layers
      # requires input images to be divisible by the average pooling size and we
      # can use `MODEL.PANOPTIC_DEEPLAB.SIZE_DIVISIBILITY` to pad all images to
      # a fixed resolution (e.g. 640x640 for COCO) to avoid having a image size
      # that is not divisible by ASPP average pooling size.
      cfg.MODEL.PANOPTIC_DEEPLAB.SIZE_DIVISIBILITY = -1
      # Only evaluates network speed (ignores post-processing).
      cfg.MODEL.PANOPTIC_DEEPLAB.BENCHMARK_NETWORK_SPEED = False
  
label_desc: Use image node_id 1 for calling a global function with example usage: add_panoptic_deeplab_config(cfg) without return types