code: def preprocess_hiddenoutput(classifier_model, current_cases, backend):
      """
      Preprocess function to extract the softmax layer of a classifier (with the HiddenOutput utility function).
      """
      _, _, data_params = current_cases["data"]
      _, input_dim = data_params["data_shape"]
  
      if backend == "tensorflow":
          model = HiddenOutput_tf(
              classifier_model, layer=-1, input_shape=(None, input_dim)
          )
          preprocess_fn = partial(preprocess_drift_tf, model=model)
      elif backend in ("pytorch", "keops"):
          model = HiddenOutput_pt(classifier_model, layer=-1)
          device = torch.device(
              "cuda" if torch.cuda.is_available() else "cpu"
          )
          preprocess_fn = partial(
              preprocess_drift_pt, model=model, device=device
          )
      else:
          pytest.skip(
              "`preprocess_hiddenoutput` only implemented for tensorflow, pytorch and keops."
          )
      return preprocess_fn
  
imports: from functools import partial
  from importlib import import_module
  import numpy
  import tensorflow
  import torch
  import torch.nn
  from sklearn.ensemble import RandomForestClassifier
  from xgboost import XGBClassifier
  from requests.exceptions import HTTPError
  import pytest
  from pytest_cases import fixture, parametrize
  from transformers import AutoTokenizer
  from alibi_detect.cd.pytorch import UAE
  from alibi_detect.cd.pytorch import preprocess_drift
  from alibi_detect.cd.tensorflow import UAE
  from alibi_detect.cd.tensorflow import preprocess_drift
  from alibi_detect.utils.pytorch.kernels import GaussianRBF
  from alibi_detect.utils.pytorch.kernels import DeepKernel
  from alibi_detect.utils.tensorflow.kernels import GaussianRBF
  from alibi_detect.utils.tensorflow.kernels import DeepKernel
  from alibi_detect.models.pytorch import TransformerEmbedding
  from alibi_detect.models.tensorflow import TransformerEmbedding
  from alibi_detect.cd.pytorch import HiddenOutput
  from alibi_detect.cd.tensorflow import HiddenOutput
  from alibi_detect.utils.frameworks import has_keops
label_desc: Use image node_id 13 for calling a global function with example usage: preprocess_hiddenoutput(classifier_model, current_cases, backend) and returns: preprocess_fn