code: def test_cov_shape_inference(
      distribution: ProbabilityDistribution,
      kernel: krn.Kernel,
      inducing_variable: iv.InducingVariables,
  ) -> None:
      assert isinstance(
          distribution, (Gaussian, DiagonalGaussian, MarkovGaussian)
      )
      gauss_tuple = (distribution.mu, distribution.cov)
      _check((gauss_tuple, (kernel, inducing_variable)))
      if isinstance(distribution, MarkovGaussian):
          _check((gauss_tuple, None, (kernel, inducing_variable)))
  
imports: from typing import Any, Callable, Iterable, Mapping, Optional, Sequence
  import numpy
  import pytest
  import tensorflow
  from numpy.testing import assert_allclose
  from tensorflow import convert_to_tensor
  import gpflow
  import gpflow.inducing_variables
  import gpflow.kernels
  from gpflow import mean_functions
  from gpflow.base import AnyNDArray
  from gpflow.config import default_float
  from gpflow.expectations import expectation, quadrature_expectation
  from gpflow.probability_distributions import DiagonalGaussian, Gaussian, MarkovGaussian, ProbabilityDistribution
label_desc: Use image node_id 20 for calling a global function with example usage: test_cov_shape_inference(distribution, kernel, inducing_variable) without return types