code: def test_clfdrift(clfdrift_params):
      backend = clfdrift_params
      if backend.lower() == "pytorch":
          model = pytorch_model(n_features)
      elif backend.lower() == "tensorflow":
          model = tensorflow_model((n_features,))
      elif backend.lower() == "sklearn":
          model = sklearn_model()
      else:
          model = None
      x_ref = np.random.randn(*(n, n_features))
  
      try:
          cd = ClassifierDrift(
              x_ref=x_ref, model=model, backend=backend
          )
      except NotImplementedError:
          cd = None
  
      if backend.lower() == "pytorch":
          assert isinstance(cd._detector, ClassifierDriftTorch)
      elif backend.lower() == "tensorflow":
          assert isinstance(cd._detector, ClassifierDriftTF)
      elif backend.lower() == "sklearn":
          assert isinstance(cd._detector, ClassifierDriftSklearn)
      else:
          assert cd is None
  
file_path: alibi-detect/alibi_detect/cd/tests/test_classifier.py
imports: import numpy
  import pytest
  import tensorflow
  from tensorflow.keras.layers import Dense, Input
  import torch
  import torch.nn
  from alibi_detect.cd import ClassifierDrift
  from alibi_detect.cd.pytorch.classifier import ClassifierDriftTorch
  from alibi_detect.cd.tensorflow.classifier import ClassifierDriftTF
  from alibi_detect.cd.sklearn.classifier import ClassifierDriftSklearn
  from sklearn.neural_network import MLPClassifier
  from typing import Tuple
label_desc: Use image node_id 5 for calling a global function with example usage: test_clfdrift(clfdrift_params) without return types