code: def unmap(data, count, inds, fill=0):
      """Unmap a subset of item (data) back to the original set of items (of size
      count)"""
      if data.dim() == 1:
          ret = data.new_full((count,), fill)
          ret[inds.type(torch.bool)] = data
      else:
          new_size = (count,) + data.size()[1:]
          ret = data.new_full(new_size, fill)
          ret[inds.type(torch.bool), :] = data
      return ret
  
imports: from functools import partial
  from typing import List, Optional, Sequence, Tuple, Union
  import numpy
  import torch
  from mmengine.structures import InstanceData
  from mmengine.utils import digit_version
  from six.moves import map, zip
  from torch import Tensor
  from torch.autograd import Function
  from torch.nn import functional
  from mmdet.structures import SampleList
  from mmdet.structures.bbox import BaseBoxes, get_box_type, stack_boxes
  from mmdet.structures.mask import BitmapMasks, PolygonMasks
  from mmdet.utils import OptInstanceList
label_desc: Use image node_id 5 for calling a global function with example usage: unmap(data, count, inds, fill) and returns: ret