code: def _get_nested_value(dic: dict, keys: list) -> Any:
      """
      Get a value from a nested dictionary.
  
      Parameters
      ----------
      dic
          The dictionary.
      keys
          List of keys to "walk" to nested value.
          For example, to extract the value `dic['key1']['key2']['key3']`, set `keys = ['key1', 'key2', 'key3']`.
  
      Returns
      -------
      The nested value specified by `keys`.
      """
      for key in keys:
          try:
              dic = dic[key]
          except (TypeError, KeyError):
              return None
      return dic
  
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 10 for calling a global function with example usage: _get_nested_value(dic, keys) and returns: dic, None