code: def transpose_and_flatten(input):
      if input.dim() > 2:
          input = input.view(
              input.size(0), input.size(1), -1
          )  # N,C,H,W => N,C,H*W
          input = input.transpose(1, 2)  # N,C,H*W => N,H*W,C
          input = input.contiguous().view(
              -1, input.size(2)
          )  # N,H*W,C => N*H*W,C
      return input
  
imports: import dataclasses
  import math
  import warnings
  from collections import defaultdict
  import numpy
  import torch
  from sklearn.metrics import confusion_matrix, auc
  from baal.utils.array_utils import to_prob
label_desc: Use image node_id 1 for calling a global function with example usage: transpose_and_flatten(input) and returns: input