code: def _assert_kl_compatible(marginal, other):
      if isinstance(
          marginal, mvn_linear_operator.MultivariateNormalLinearOperator
      ) and isinstance(
          other, mvn_linear_operator.MultivariateNormalLinearOperator
      ):
          return
      raise ValueError(
          "Attempting to compute KL between a GP marginal and a distribution of "
          "incompatible type. GP marginal has type {} and other distribution has "
          "type {}.".format(type(marginal), type(other))
      )
  
imports: import functools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import cholesky_util
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import mvn_linear_operator
  from tensorflow_probability.python.distributions.internal import stochastic_process_util
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import batch_shape_lib
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import linalg
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import nest
label_desc: Use image node_id 2 for calling a global function with example usage: _assert_kl_compatible(marginal, other) without return types