code: def testLogBesselIveGradient(self, dtype, tol):
      v = tf.constant([-0.2, -1.0, 1.0, 0.5, 2.0], dtype=dtype)[
          ..., tf.newaxis
      ]
      z = tf.constant([0.3, 0.5, 0.9, 1.0, 12.0, 22.0], dtype=dtype)
  
      err = self.compute_max_gradient_error(
          functools.partial(bessel.log_bessel_ive, v), [z]
      )
      self.assertLess(err, tol)
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  from scipy import constants
  from scipy import special
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import bessel
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.bessel import _compute_general_continued_fraction
label_desc: Use image node_id 20 for calling the BesselIveTest obj's underlying member method code with example usage: obj.testLogBesselIveGradient(dtype, tol) without return types