code: def load_text_embed(
      filepath: Union[str, os.PathLike], load_dir: str = "model"
  ) -> Tuple[TransformerEmbedding, Callable]:
      """Legacy function to load text embedding."""
      model_dir = Path(filepath).joinpath(load_dir)
      tokenizer = AutoTokenizer.from_pretrained(
          str(model_dir.resolve())
      )
      args = dill.load(open(model_dir.joinpath("embedding.dill"), "rb"))
      emb = TransformerEmbedding(
          str(model_dir.resolve()),
          embedding_type=args["embedding_type"],
          layers=args["layers"],
      )
      return emb, tokenizer
  
imports: import logging
  import os
  from importlib import import_module
  import warnings
  from functools import partial
  from pathlib import Path
  from typing import Callable, Dict, List, Optional, Tuple, Union, Type
  import dill
  import tensorflow
  from tensorflow_probability.python.distributions.distribution import Distribution
  from transformers import AutoTokenizer
  from alibi_detect.ad import AdversarialAE, ModelDistillation
  from alibi_detect.ad.adversarialae import DenseHidden
  from alibi_detect.cd import ChiSquareDrift, ClassifierDrift, KSDrift, MMDDrift, TabularDrift
  from alibi_detect.cd.tensorflow import UAE, HiddenOutput
  from alibi_detect.cd.tensorflow.preprocess import _Encoder
  from alibi_detect.models.tensorflow import PixelCNN, TransformerEmbedding
  from alibi_detect.models.tensorflow.autoencoder import AE, AEGMM, VAE, VAEGMM, DecoderLSTM, EncoderLSTM, Seq2Seq
  from alibi_detect.od import LLR, IForest, Mahalanobis, OutlierAE, OutlierAEGMM, OutlierProphet, OutlierSeq2Seq, OutlierVAE, OutlierVAEGMM, SpectralResidual
  from alibi_detect.od.llr import build_model
  from alibi_detect.utils.tensorflow.kernels import DeepKernel
  from alibi_detect.utils.frameworks import Framework
  from alibi_detect.version import __version__
  from alibi_detect.base import Detector
  from alibi_detect.saving._typing import VALID_DETECTORS
label_desc: Use image node_id 21 for calling a global function with example usage: load_text_embed(filepath, load_dir) and returns: emb,  tokenizer