code: def test_reliability_experiment(
      self, nfeatures, nlabels, nsamples, tolerance=0.05
  ):
      data, labels, weights, bias = self._generate_linear_dataset(
          nfeatures, nlabels, nsamples
      )
  
      nreplicates = 5
      perturbations = np.linspace(0.0, 3.0, 10)
      reliability = []
  
      for i, perturbation in enumerate(perturbations):
          reliability_replicates = tf.stack(
              [
                  self._compute_perturbed_reliability(
                      data, labels, weights, bias, perturbation
                  )
                  for _ in range(nreplicates)
              ],
              axis=0,
          )
          reliability.append(
              tf.math.reduce_mean(reliability_replicates, axis=0)
          )
      reliability = self.evaluate(tf.stack(reliability, axis=0))
  
      for i in range(1, len(reliability)):
          logging.info(
              "Reliability at perturbation %.3f: %.4f",
              perturbations[i],
              reliability[i],
          )
          self.assertLessEqual(
              reliability[i - 1],
              reliability[i] + tolerance,
              msg="Reliability decreases (%.4f to %.4f + %.3f) "
              "with perturbation size increasing from %.4f "
              "to %.4f"
              % (
                  reliability[i - 1],
                  reliability[i],
                  tolerance,
                  perturbations[i - 1],
                  perturbations[i],
              ),
          )
  
imports: import itertools
  from absl import logging
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import calibration
label_desc: Use image node_id 5 for calling the CalibrationTest obj's underlying member method code with example usage: obj.test_reliability_experiment(nfeatures, nlabels, nsamples, tolerance) without return types