code: def test_diag(
      Xdata: tf.Tensor,
      Xnew: tf.Tensor,
      kernel: Kernel,
      mu: tf.Tensor,
      sqrt: tf.Tensor,
      chol: tf.Tensor,
      white: bool,
  ) -> None:
      Fstar_mean_1, Fstar_var_1 = conditional(
          Xnew, Xdata, kernel, mu, q_sqrt=sqrt, white=white
      )
      Fstar_mean_2, Fstar_var_2 = conditional(
          Xnew, Xdata, kernel, mu, q_sqrt=chol, white=white
      )
  
      mean_diff = Fstar_mean_1 - Fstar_mean_2
      var_diff = Fstar_var_1 - Fstar_var_2
  
      assert_allclose(mean_diff, 0)
      assert_allclose(var_diff, 0)
  
imports: import numpy
  import pytest
  import tensorflow
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow import Parameter
  from gpflow.base import AnyNDArray, MeanAndVariance
  from gpflow.conditionals import conditional
  from gpflow.config import default_float
  from gpflow.kernels import Kernel
  from gpflow.utilities.bijectors import triangular
label_desc: Use image node_id 7 for calling a global function with example usage: test_diag(Xdata, Xnew, kernel, mu, sqrt, chol, white) without return types