code: def Kuf_separate_linear_coregionalization(
      inducing_variable: SeparateIndependentInducingVariables,
      kernel: LinearCoregionalization,
      Xnew: TensorType,
  ) -> 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}."
  
      return tf.stack(
          [
              Kuf(f, k, Xnew)
              for f, k in zip(
                  inducing_variable.inducing_variable_list,
                  kernel.kernels,
              )
          ],
          axis=0,
      )
  
file_path: GPflow/gpflow/covariances/multioutput/kufs.py
imports: from typing import Callable, Union
  import tensorflow
  from check_shapes import check_shapes
  from ...base import TensorType
  from ...inducing_variables import FallbackSeparateIndependentInducingVariables, FallbackSharedIndependentInducingVariables, InducingPoints, SeparateIndependentInducingVariables, SharedIndependentInducingVariables
  from ...kernels import LinearCoregionalization, MultioutputKernel, SeparateIndependent, SharedIndependent
  from ..dispatch import Kuf
label_desc: Use image node_id 10 for calling a global function with example usage: Kuf_separate_linear_coregionalization(inducing_variable, kernel, Xnew) and returns: tf