code: def test_preconditioner(self):
      xs = self.evaluate(
          tf.random.uniform([30, 30], seed=test_util.test_seed())
      )
      cov_linop = tf.linalg.LinearOperatorFullMatrix(
          tf.matmul(xs, xs, transpose_b=True)
          + tf.linalg.eye(30) * 1e-3,
          is_self_adjoint=True,
          is_positive_definite=True,
      )
  
      auto_ct_mvn_prec_linop = (
          auto_composite_tensor.auto_composite_tensor(
              mvnpflo.MultivariateNormalPrecisionFactorLinearOperator,
              non_identifying_kwargs=("name",),
          )
      )
      tril = AutoTriL(**cov_linop.cholesky().parameters)
      momentum_distribution = auto_ct_mvn_prec_linop(
          precision_factor=tril
      )
  
      def body(d):
          return (
              d.copy(
                  precision_factor=AutoTriL(
                      **dict(
                          d.precision_factor.parameters,
                          tril=d.precision_factor.to_dense()
                          + tf.linalg.eye(30),
                      )
                  )
              ),
          )
  
      after_loop = tf.while_loop(
          lambda d: True,
          body,
          (momentum_distribution,),
          maximum_iterations=1,
      )
      tf.nest.map_structure(
          self.evaluate, after_loop, expand_composites=True
      )
  
imports: import functools
  import os
  from absl import flags
  from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import reshape
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import transform_diagonal
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.distributions import mvn_precision_factor_linop
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import test_util
  from absl.testing import absltest
label_desc: Use image node_id 7 for calling the AutoCompositeTensorTest obj's underlying member method code with example usage: obj.test_preconditioner() and returns: d