code: def test_chandrupatla_float64_high_precision(self):
      expected_roots = samplers.normal(
          [4, 3],
          seed=test_util.test_seed(sampler_type="stateless"),
          dtype=tf.float64,
      )
      tolerance = 1e-12
      roots, value_at_roots, _ = root_search.find_root_chandrupatla(
          objective_fn=lambda x: (x - expected_roots) ** 3,
          low=tf.convert_to_tensor(-100.0, dtype=expected_roots.dtype),
          high=tf.convert_to_tensor(100.0, dtype=expected_roots.dtype),
          position_tolerance=tolerance,
      )
      self.assertAllClose(roots, expected_roots, atol=tolerance)
      self.assertAllClose(value_at_roots, tf.zeros_like(value_at_roots))
  
imports: import numpy
  import scipy.optimize
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import special_math
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import root_search
label_desc: Use image node_id 5 for calling the ChandrupatlaRootSearchTest obj's underlying member method code with example usage: obj.test_chandrupatla_float64_high_precision() without return types