code: def _load_kernel_config(
      cfg: dict, backend: str = Framework.TENSORFLOW
  ) -> Callable:
      """
      Loads a kernel from a kernel config dict.
  
      Parameters
      ----------
      cfg
          A kernel config dict. (see pydantic schema's).
      backend
          The backend.
  
      Returns
      -------
      The kernel.
      """
      if backend == Framework.TENSORFLOW:
          kernel = load_kernel_config_tf(cfg)
      elif backend == Framework.PYTORCH:
          kernel = load_kernel_config_pt(cfg)
      else:  # backend=='keops'
          kernel = load_kernel_config_ke(cfg)
      return kernel
  
imports: import logging
  import os
  from functools import partial
  from importlib import import_module
  from pathlib import Path
  from typing import Any, Callable, Optional, Union, Type, TYPE_CHECKING
  import dill
  import numpy
  import toml
  from transformers import AutoTokenizer
  from alibi_detect.saving.registry import registry
  from alibi_detect.saving._tensorflow import load_detector_legacy, load_embedding_tf, load_kernel_config_tf, load_model_tf, load_optimizer_tf, prep_model_and_emb_tf, get_tf_dtype
  from alibi_detect.saving._pytorch import load_embedding_pt, load_kernel_config_pt, load_model_pt, load_optimizer_pt, prep_model_and_emb_pt, get_pt_dtype
  from alibi_detect.saving._keops import load_kernel_config_ke
  from alibi_detect.saving._sklearn import load_model_sk
  from alibi_detect.saving.validate import validate_config
  from alibi_detect.base import Detector, ConfigurableDetector, StatefulDetectorOnline
  from alibi_detect.utils.frameworks import has_tensorflow, has_pytorch, Framework
  from alibi_detect.saving.schemas import supported_models_tf, supported_models_torch
  from alibi_detect.utils.missing_optional_dependency import import_optional
label_desc: Use image node_id 4 for calling a global function with example usage: _load_kernel_config(cfg, backend) and returns: kernel