code: def Kuu_fallbace_separate(
      inducing_variable: FallbackSeparateIndependentInducingVariables,
      kernel: Union[SeparateIndependent, LinearCoregionalization],
      *,
      jitter: float = 0.0,
  ) -> tf.Tensor:
      n_iv = len(inducing_variable.inducing_variable_list)
      n_k = len(kernel.kernels)
      assert (
          n_iv == n_k
      ), f"Must have same number of inducing variables and kernels. Found {n_iv} and {n_k}."
  
      Kmms = [
          Kuu(f, k)
          for f, k in zip(
              inducing_variable.inducing_variable_list, kernel.kernels
          )
      ]
      Kmm = tf.stack(Kmms, axis=0)
      jittermat = (
          tf.eye(inducing_variable.num_inducing, dtype=Kmm.dtype)[
              None, :, :
          ]
          * jitter
      )
      return Kmm + jittermat
  
file_path: GPflow/gpflow/covariances/multioutput/kuus.py
imports: from typing import Union
  import tensorflow
  from check_shapes import check_shapes
  from ...inducing_variables import FallbackSeparateIndependentInducingVariables, FallbackSharedIndependentInducingVariables, InducingPoints
  from ...kernels import IndependentLatent, LinearCoregionalization, MultioutputKernel, SeparateIndependent, SharedIndependent
  from ..dispatch import Kuu
label_desc: Use image node_id 5 for calling a global function with example usage: Kuu_fallbace_separate(inducing_variable, kernel) and returns: unknown