code: def window_reverse(
      windows, window_size: Tuple[int, int], img_size: Tuple[int, int]
  ):
      H, W = img_size
      C = windows.shape[-1]
      x = windows.view(
          -1,
          H // window_size[0],
          W // window_size[1],
          window_size[0],
          window_size[1],
          C,
      )
      x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, H, W, C)
      return x
  
imports: import math
  from functools import partial
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.utils.checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import DropPath, to_2tuple, to_ntuple, Mlp, ClassifierHead, LayerNorm2d, get_attn, get_act_layer, get_norm_layer, RelPosBias, _assert
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_function
  from ._manipulate import named_apply
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 2 for calling a global function with example usage: window_reverse(windows, window_size, img_size) and returns: x