code: def window_partition(x, window_size):
      """
      Args:
          x: (B, H, W, C)
          window_size (int): window size
  
      Returns:
          windows: (num_windows*B, window_size, window_size, C)
      """
      B, H, W, C = x.shape
      x = x.view(
          B,
          H // window_size,
          window_size,
          W // window_size,
          window_size,
          C,
      )
      windows = (
          x.permute(0, 1, 3, 2, 4, 5)
          .contiguous()
          .view(-1, window_size, window_size, C)
      )
      return windows
  
imports: from collections import OrderedDict
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from torch import Tensor
  from .common import EncoderModule, _take, make_n_channel_input
  from ..activations import get_activation_block, ACT_GELU
  from timm.models.layers import DropPath, to_2tuple, trunc_normal_
label_desc: Use image node_id 1 for calling a global function with example usage: window_partition(x, window_size) and returns: windows