code: def test_docstring_simple(self):
      label = tf.cast([0, 0, 1, 0, 1, 1], dtype=tf.bool)
      log_pred = tf.math.log([0.1, 0.05, 0.5, 0.2, 0.99, 0.99])
      ece, acc, conf, cnt, edges, buckets = self.evaluate(
          calibration.expected_calibration_error_quantiles(
              label, log_pred, num_buckets=3
          )
      )
      self.assertNear(0.145, ece, err=1e-6)
      self.assertAllClose([0.0, 0.0, 1.0], acc, rtol=1e-6, atol=1e-6)
      self.assertAllClose(
          [0.075, 0.2, 0.826667], conf, rtol=1e-6, atol=0.0
      )
      self.assertAllClose([2.0, 1.0, 3.0], cnt, rtol=1e-6, atol=0.0)
      self.assertAllClose(
          tf.math.log([0.05, 0.2, 0.5, 0.99]),
          edges,
          rtol=1e-6,
          atol=0.0,
      )
      self.assertAllEqual([0, 0, 2, 1, 2, 2], buckets)
  
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 1 for calling the ExpectedCalibrationErrorQuantiles obj's underlying member method code with example usage: obj.test_docstring_simple() without return types