class_docstr: Most tests done in the base class LinearOperatorDerivedClassTest.
  
  In this test, the operator is constructed with hints that invoke the use of
  a Cholesky decomposition for solves/determinant.
code: def test_is_x_flags(self):
      # Matrix with two positive eigenvalues.
      matrix = [[1.0, 0.0], [0.0, 7.0]]
      operator = linalg.LinearOperatorFullMatrix(
          matrix, is_positive_definite=True, is_self_adjoint=True
      )
  
      self.assertTrue(operator.is_positive_definite)
      self.assertTrue(operator.is_self_adjoint)
  
      # Should be auto-set
      self.assertTrue(operator.is_non_singular)
      self.assertTrue(operator._can_use_cholesky)
      self.assertTrue(operator.is_square)
  
imports: import numpy
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.linalg import linalg
  from tensorflow.python.ops.linalg import linear_operator_test_util
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the SquareLinearOperatorFullMatrixSymmetricPositiveDefiniteTest obj's underlying member method code with example usage: obj.test_is_x_flags() without return types