code: def testBatesMean(self):
      # TODO(b/157666350): Turn this into a hypothesis test.
      bounds = np.array(
          [[0.0, 1.0], [1.0, 2.0], [-2.0, -1.0], [10.0, 20.0]]
      )
      b = bates.Bates(
          total_count=10.0,
          low=bounds[..., 0],
          high=bounds[..., 1],
          validate_args=True,
      )
      self.assertAllClose(bounds.mean(1), self.evaluate(b.mean()))
  
imports: import fractions
  import math
  import sys
  from absl.testing import parameterized
  import hypothesis
  import hypothesis.strategies
  import numpy
  import scipy
  import scipy.integrate
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bates
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 22 for calling the BatesTest obj's underlying member method code with example usage: obj.testBatesMean() without return types