code: def reverse_correct_unfold_reduction_order(x):
      out_channel, in_channel = x.shape
      x = x.reshape(out_channel, in_channel // 4, 4)
      x = (
          x[:, :, [0, 2, 1, 3]]
          .transpose(1, 2)
          .reshape(out_channel, in_channel)
      )
  
      return x
  
file_path: transformers/src/transformers/models/upernet/convert_swin_upernet_to_pytorch.py
imports: import argparse
  import json
  import requests
  import torch
  from huggingface_hub import hf_hub_download
  from PIL import Image
  from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
label_desc: Use image node_id 6 for calling a global function with example usage: reverse_correct_unfold_reduction_order(x) and returns: x