code: def test_cholesky(self):
      z = random_ops.random_normal([2, 3, 3])
      x = math_ops.matmul(
          z, array_ops.matrix_transpose(z)
      ) + linalg_ops.eye(  # Ensure pos. def.
          3
      )  # Ensure well-conditioned.
  
      def loop_fn(i):
          return linalg_ops.cholesky(array_ops.gather(x, i))
  
      self._test_loop_fn(loop_fn, 2)
  
imports: import itertools
  from absl.testing import parameterized
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import clip_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import special_math_ops
  from tensorflow.python.ops import tensor_array_grad
  from tensorflow.python.ops.parallel_for import control_flow_ops
  from tensorflow.python.ops.parallel_for.test_util import PForTestCase
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the LinalgTest obj's underlying member method code with example usage: obj.test_cholesky() and returns: linalg_ops