code: def destructure_tensor(
      client_batch: List[int],
      result_tensor: torch.Tensor,
  ) -> List[torch.Tensor]:
      start = 0
      res_list: List[torch.Tensor] = []
  
      for elems in client_batch:
          end = start + elems
          res_list.append(result_tensor.narrow(0, start, elems))
          start = end
  
      return res_list
  
imports: from typing import Any, Dict, List, Optional, Tuple
  import torch
  from pytext.torchscript.tensorizer.tensorizer import ScriptTensorizer
label_desc: Use image node_id 12 for calling a global function with example usage: destructure_tensor(client_batch, result_tensor) and returns: res_list