code: def apply_byte_permutation(
      batch: List[Mapping[str, Tensor]], opts: argparse.Namespace
  ) -> List[Mapping[str, Tensor]]:
      """
      Apply the BytePermutation transform to each batch element.
  
      Args:
          batch: The batch of data.
          opts: The global arguments.
  
      Returns:
          The modified batch.
      """
      if getattr(opts, "image_augmentation.byte_permutation.enable"):
          transform = image_bytes.BytePermutation(opts)
          for i, elem in enumerate(batch):
              batch[i] = transform(elem)
      return batch
  
file_path: ml-cvnets/data/collate_fns/byteformer_collate_functions.py
imports: import argparse
  from typing import Dict, List, Mapping, Optional, Union
  import torch
  from torch import Tensor
  from torch.nn import functional
  from data.collate_fns import COLLATE_FN_REGISTRY, collate_functions
  from data.transforms import audio_bytes, image_bytes
label_desc: Use image node_id 7 for calling a global function with example usage: apply_byte_permutation(batch, opts) and returns: batch