code: def swin_converter(ckpt):
      new_ckpt = OrderedDict()
  
      def correct_unfold_reduction_order(x):
          out_channel, in_channel = x.shape
          x = x.reshape(out_channel, 4, in_channel // 4)
          x = (
              x[:, [0, 2, 1, 3], :]
              .transpose(1, 2)
              .reshape(out_channel, in_channel)
          )
          return x
  
      def correct_unfold_norm_order(x):
          in_channel = x.shape[0]
          x = x.reshape(4, in_channel // 4)
          x = x[[0, 2, 1, 3], :].transpose(0, 1).reshape(in_channel)
          return x
  
      for k, v in ckpt.items():
          if k.startswith("head"):
              continue
          elif k.startswith("layers"):
              new_v = v
              if "attn." in k:
                  new_k = k.replace("attn.", "attn.w_msa.")
              elif "mlp." in k:
                  if "mlp.fc1." in k:
                      new_k = k.replace("mlp.fc1.", "ffn.layers.0.0.")
                  elif "mlp.fc2." in k:
                      new_k = k.replace("mlp.fc2.", "ffn.layers.1.")
                  else:
                      new_k = k.replace("mlp.", "ffn.")
              elif "downsample" in k:
                  new_k = k
                  if "reduction." in k:
                      new_v = correct_unfold_reduction_order(v)
                  elif "norm." in k:
                      new_v = correct_unfold_norm_order(v)
              else:
                  new_k = k
              new_k = new_k.replace("layers", "stages", 1)
          elif k.startswith("patch_embed"):
              new_v = v
              if "proj" in k:
                  new_k = k.replace("proj", "projection")
              else:
                  new_k = k
          else:
              new_v = v
              new_k = k
  
          new_ckpt["backbone." + new_k] = new_v
  
      return new_ckpt
  
imports: import warnings
  from collections import OrderedDict
  from copy import deepcopy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from mmcv.cnn import build_norm_layer
  from mmcv.cnn.bricks.transformer import FFN, build_dropout
  from mmengine.logging import MMLogger
  from mmengine.model import BaseModule, ModuleList
  from mmengine.model.weight_init import constant_init, trunc_normal_, trunc_normal_init
  from mmengine.runner.checkpoint import CheckpointLoader
  from mmengine.utils import to_2tuple
  from mmdet.registry import MODELS
  from ..layers import PatchEmbed, PatchMerging
label_desc: Use image node_id 1 for calling a global function with example usage: swin_converter(ckpt) and returns: new_ckpt, x, x