code: def test_lsdddriftonline(lsdddriftonline_params):
      backend = lsdddriftonline_params
      x_ref = np.random.randn(*(n, n_features))
  
      try:
          cd = LSDDDriftOnline(
              x_ref=x_ref,
              ert=25,
              window_size=5,
              backend=backend,
              n_bootstraps=100,
          )
      except NotImplementedError:
          cd = None
  
      if backend.lower() == "pytorch":
          assert isinstance(cd._detector, LSDDDriftOnlineTorch)
      elif backend.lower() == "tensorflow":
          assert isinstance(cd._detector, LSDDDriftOnlineTF)
      else:
          assert cd is None
          return None
  
      # Test predict
      x_t = np.random.randn(n_features)
      t0 = cd.t
      cd.predict(x_t)
      assert (
          cd.t - t0 == 1
      )  # This checks state updated (self.t at least)
  
      # Test score
      t0 = cd.t
      cd.score(x_t)
      assert cd.t - t0 == 1
  
imports: import numpy
  import pytest
  from alibi_detect.cd import LSDDDriftOnline
  from alibi_detect.cd.pytorch.lsdd_online import LSDDDriftOnlineTorch
  from alibi_detect.cd.tensorflow.lsdd_online import LSDDDriftOnlineTF
label_desc: Use image node_id 2 for calling a global function with example usage: test_lsdddriftonline(lsdddriftonline_params) and returns: None