code: def window_reverse(windows, window_size, H, W):
      """
      Args:
          windows: (num_windows*B, window_size, window_size, C)
          window_size (int): Window size
          H (int): Height of image
          W (int): Width of image
      Returns:
          x: (B, H, W, C)
      """
      B = int(windows.shape[0] / (H * W / window_size / window_size))
      x = windows.view(
          B,
          H // window_size,
          W // window_size,
          window_size,
          window_size,
          -1,
      )
      x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1)
      return x
  
imports: from collections import OrderedDict
  import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  import numpy
  from timm.models.layers import DropPath, to_2tuple, trunc_normal_
  from annotator.uniformer.mmcv_custom import load_checkpoint
  from annotator.uniformer.mmseg.utils import get_root_logger
  from ..builder import BACKBONES
label_desc: Use image node_id 2 for calling a global function with example usage: window_reverse(windows, window_size, H, W) and returns: x