code: def kernel() -> Kernel:
      k = gpflow.kernels.Matern32() + gpflow.kernels.White()
      k.kernels[1].variance.assign(0.01)
      return k
  
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 1 for calling a global function with example usage: kernel() and returns: k