code: def _verifyCholeskyBase(self, x, chol, verification):
      chol_np, verification_np = self.evaluate([chol, verification])
      self.assertAllClose(x, verification_np)
      self.assertShapeEqual(x, chol)
      # Check that the cholesky is lower triangular, and has positive diagonal
      # elements.
      if chol_np.shape[-1] > 0:
          chol_reshaped = np.reshape(
              chol_np, (-1, chol_np.shape[-2], chol_np.shape[-1])
          )
          for chol_matrix in chol_reshaped:
              self.assertAllClose(chol_matrix, np.tril(chol_matrix))
              self.assertTrue((np.diag(chol_matrix) > 0.0).all())
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.linalg import linalg
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the CholeskyOpTest obj's underlying member method code with example usage: obj._verifyCholeskyBase(x, chol, verification) without return types