code: def last_zero_init(m):
      if isinstance(m, nn.Sequential):
          constant_init(m[-1], val=0)
      else:
          constant_init(m, val=0)
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import ConvModule, Scale, bias_init_with_prob, normal_init, DepthwiseSeparableConvModule
  from mmcv.cnn import constant_init, kaiming_init
  from mmcv.runner import force_fp32
  from mmdet.core import anchor_inside_flags, bbox2distance, bbox_overlaps, build_assigner, build_sampler, distance2bbox, distance2kps, kps2distance, images_to_levels, multi_apply, multiclass_nms, reduce_mean, unmap
  from ..builder import HEADS, build_loss
  from .anchor_head import AnchorHead
  from .base_dense_head import BaseDenseHead
  from .dense_test_mixins import BBoxTestMixin
label_desc: Use image node_id 1 for calling a global function with example usage: last_zero_init(m) without return types