code: def _ensure_transform_function(
      self, module_name: str, transform_script_path: str
  ) -> _TransformFunction:
      module_name = "cpm_live.transforms.{}".format(module_name)
      if transform_script_path not in self._transform_func_table:
          loader = importlib.machinery.SourceFileLoader(
              module_name, transform_script_path
          )
          spec = importlib.util.spec_from_loader(loader.name, loader)
          if spec is None:
              raise RuntimeError("spec is none! {}".format(module_name))
          mod = importlib.util.module_from_spec(spec)
          self._transform_func_table[transform_script_path] = {
              "loader": loader,
              "module": mod,
              "last_m": 0,
          }
  
      transform_script_info = self._transform_func_table[
          transform_script_path
      ]
      curr_m_time = float(
          transform_script_info["loader"].path_stats(
              transform_script_path
          )["mtime"]
      )
      if curr_m_time > transform_script_info["last_m"]:
          transform_script_info["last_m"] = curr_m_time
          transform_script_info["loader"].exec_module(
              transform_script_info["module"]
          )
      transform_func = getattr(
          transform_script_info["module"], "transform", None
      )
      if transform_func is None:
  
          def _empty_transform_func(
              data: CPMBeeInputType, num_sample: int, r: random.Random
          ):
              raise NotImplementedError(
                  "Transform func for dataset {} not implemented".format(
                      module_name
                  )
              )
  
          return _empty_transform_func
      else:
          return transform_func
  
imports: from collections import OrderedDict
  import multiprocessing
  import os
  from queue import Empty
  from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
  from typing_extensions import TypedDict
  from ...dataset import DistributedDataset
  from ...tokenizers import CPMBeeTokenizer
  from ...utils.config import load_dataset_config
  import numpy
  import time
  from numpy.typing import NDArray
  import torch
  import bmtrain
  import importlib.machinery
  import importlib.util
  import types
  import random
label_desc: Use image node_id 5 for calling the _MixedDatasetBatchPacker obj's underlying member method code with example usage: obj._ensure_transform_function(module_name, transform_script_path) and returns: _empty_transform_func, transform_func