code: def test_inducing_variables_psd_schur(
      input_dim: int,
      inducing_variable: InducingVariables,
      kernel: Kernel,
  ) -> None:
      # Conditional variance must be PSD.
      X = np.random.randn(5, input_dim)
      Kuf_values = Kuf(inducing_variable, kernel, X)
      Kuu_values = Kuu(
          inducing_variable, kernel, jitter=default_jitter()
      )
      Kff_values = kernel(X)
      Qff_values = Kuf_values.numpy().T @ np.linalg.solve(
          Kuu_values, Kuf_values
      )
      assert np.all(np.linalg.eig(Kff_values - Qff_values)[0] > 0.0)
  
file_path: GPflow/tests/gpflow/covariances/test_base_covariances.py
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow.config import default_jitter
  from gpflow.covariances import Kuf, Kuu
  from gpflow.inducing_variables import InducingPatches, InducingPoints, InducingVariables, Multiscale
  from gpflow.kernels import Kernel
label_desc: Use image node_id 4 for calling a global function with example usage: test_inducing_variables_psd_schur(input_dim, inducing_variable, kernel) without return types