code: def testJacobianWithTensors(self):
      bijector = cholesky_to_inv_cholesky.CholeskyToInvCholesky()
      x = np.array(
          [[[3.0, 0.0], [1.0, 4.0]], [[2.0, 0.0], [7.0, 1.0]]],
          dtype=np.float32,
      )
      fldj = bijector.forward_log_det_jacobian(x, event_ndims=2)
      fldj0 = bijector.forward_log_det_jacobian(x[0], event_ndims=2)
      fldj1 = bijector.forward_log_det_jacobian(x[1], event_ndims=2)
      fldj_, fldj0_, fldj1_ = self.evaluate([fldj, fldj0, fldj1])
      self.assertAllClose(fldj_[0], fldj0_, rtol=1e-5)
      self.assertAllClose(fldj_[1], fldj1_, rtol=1e-5)
  
file_path: probability/tensorflow_probability/python/bijectors/cholesky_to_inv_cholesky_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import cholesky_to_inv_cholesky
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import fill_scale_tril
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 5 for calling the CholeskyToInvCholeskyTest obj's underlying member method code with example usage: obj.testJacobianWithTensors() without return types