code: def test_clfdrift(clfdrift_params):
      (
          p_val,
          n_features,
          preds_type,
          binarize_preds,
          n_folds,
          train_size,
          preprocess_batch,
          update_x_ref,
      ) = clfdrift_params
  
      np.random.seed(0)
      torch.manual_seed(0)
  
      model = MyModel(n_features, softmax=(preds_type == "probs"))
      x_ref = np.random.randn(*(n, n_features)).astype(np.float32)
      x_test1 = np.ones_like(x_ref)
      to_list = False
      if preprocess_batch is not None:
          to_list = True
          x_ref = [_ for _ in x_ref]
          update_x_ref = None
  
      cd = ClassifierDriftTorch(
          x_ref=x_ref,
          model=model,
          p_val=p_val,
          update_x_ref=update_x_ref,
          train_size=train_size,
          n_folds=n_folds,
          preds_type=preds_type,
          binarize_preds=binarize_preds,
          preprocess_batch_fn=preprocess_batch,
          batch_size=1,
      )
  
      x_test0 = x_ref.copy()
      preds_0 = cd.predict(x_test0)
      assert cd.n == len(x_test0) + len(x_ref)
      assert preds_0["data"]["is_drift"] == 0
      assert preds_0["data"]["distance"] >= 0
  
      if to_list:
          x_test1 = [_ for _ in x_test1]
      preds_1 = cd.predict(x_test1)
      assert cd.n == len(x_test1) + len(x_test0) + len(x_ref)
      assert preds_1["data"]["is_drift"] == 1
      assert preds_1["data"]["distance"] >= 0
  
      assert preds_0["data"]["distance"] < preds_1["data"]["distance"]
      assert cd.meta["params"]["preds_type"] == preds_type
      assert cd.meta["params"]["binarize_preds "] == binarize_preds
  
file_path: alibi-detect/alibi_detect/cd/pytorch/tests/test_classifier_pt.py
imports: from itertools import product
  import numpy
  import pytest
  import torch
  import torch.nn
  from typing import Union
  from alibi_detect.cd.pytorch.classifier import ClassifierDriftTorch
label_desc: Use image node_id 3 for calling a global function with example usage: test_clfdrift(clfdrift_params) without return types