code: def window_reverse(windows, window_size, dims):
      """window reverse operation based on: "Liu et al.,
      Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
      <https://arxiv.org/abs/2103.14030>"
      https://github.com/microsoft/Swin-Transformer
  
       Args:
          windows: windows tensor.
          window_size: local window size.
          dims: dimension values.
      """
      if len(dims) == 4:
          b, d, h, w = dims
          x = windows.view(
              b,
              d // window_size[0],
              h // window_size[1],
              w // window_size[2],
              window_size[0],
              window_size[1],
              window_size[2],
              -1,
          )
          x = (
              x.permute(0, 1, 4, 2, 5, 3, 6, 7)
              .contiguous()
              .view(b, d, h, w, -1)
          )
  
      elif len(dims) == 3:
          b, h, w = dims
          x = windows.view(
              b,
              h // window_size[0],
              w // window_size[1],
              window_size[0],
              window_size[1],
              -1,
          )
          x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(b, h, w, -1)
      return x
  
imports: from __future__ import annotations
  import itertools
  from collections.abc import Sequence
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from torch.nn import LayerNorm
  from typing_extensions import Final
  from monai.networks.blocks import MLPBlock
  from monai.networks.blocks import PatchEmbed, UnetOutBlock, UnetrBasicBlock, UnetrUpBlock
  from monai.networks.layers import DropPath, trunc_normal_
  from monai.utils import ensure_tuple_rep, look_up_option, optional_import
  from monai.utils.deprecate_utils import deprecated_arg
label_desc: Use image node_id 2 for calling a global function with example usage: window_reverse(windows, window_size, dims) and returns: x