class_docstr: A instance embedding head described in :paper:`Panoptic-DeepLab`.
code: def layers(self, features):
      assert self.decoder_only
      y = super().layers(features)
      # center
      center = self.center_head(y)
      center = self.center_predictor(center)
      # offset
      offset = self.offset_head(y)
      offset = self.offset_predictor(offset)
      return center, offset
  
imports: import numpy
  from typing import Callable, Dict, List, Union
  import fvcore.nn.weight_init
  import torch
  from torch import nn
  from torch.nn import functional
  from detectron2.config import configurable
  from detectron2.data import MetadataCatalog
  from detectron2.layers import Conv2d, DepthwiseSeparableConv2d, ShapeSpec, get_norm
  from detectron2.modeling import META_ARCH_REGISTRY, SEM_SEG_HEADS_REGISTRY, build_backbone, build_sem_seg_head
  from detectron2.modeling.postprocessing import sem_seg_postprocess
  from detectron2.projects.deeplab import DeepLabV3PlusHead
  from detectron2.projects.deeplab.loss import DeepLabCE
  from detectron2.structures import BitMasks, ImageList, Instances
  from detectron2.utils.registry import Registry
  from .post_processing import get_panoptic_segmentation
label_desc: Use image node_id 4 for calling the PanopticDeepLabInsEmbedHead obj's underlying member method code with example usage: obj.layers(features) and returns: center,  offset