code: def test_mixed_shared_shape(fun: Callable[..., tf.Tensor]) -> None:
      inducing_variable = mf.SharedIndependentInducingVariables(
          make_ip()
      )
      kernel = mk.LinearCoregionalization(
          make_kernels(Datum.L), Datum.W
      )
      if fun is covariances.Kuu:
          t = tf.linalg.cholesky(
              fun(inducing_variable, kernel, jitter=1e-9)
          )
          assert t.shape == (Datum.L, Datum.M, Datum.M)
      else:
          t = fun(inducing_variable, kernel, Datum.Xnew)
          assert t.shape == (Datum.L, Datum.M, Datum.N)
  
imports: from typing import Any, Callable, Sequence
  import numpy
  import pytest
  import tensorflow
  import gpflow
  import gpflow.inducing_variables.multioutput
  import gpflow.kernels.multioutput
  from gpflow import covariances
  from gpflow.inducing_variables import InducingVariables
  from gpflow.kernels import Kernel
label_desc: Use image node_id 9 for calling a global function with example usage: test_mixed_shared_shape(fun) without return types