code: def VerifyMean(self, dim):
      num_samples = int(7e4)
      uniform = spherical_uniform.SphericalUniform(
          batch_shape=[2, 1],
          dimension=dim,
          dtype=self.dtype,
          validate_args=True,
          allow_nan_stats=False,
      )
      samples = uniform.sample(num_samples, seed=test_util.test_seed())
      true_mean = self.evaluate(uniform.mean())
      check1 = st.assert_true_mean_equal_by_dkwm(
          samples=samples,
          low=-(1.0 + 1e-7),
          high=1.0 + 1e-7,
          expected=true_mean,
          false_fail_rate=1e-6,
      )
      check2 = assert_util.assert_less(
          st.min_discrepancy_of_true_means_detectable_by_dkwm(
              num_samples,
              low=-1.0,
              high=1.0,
              # Smaller false fail rate because of different batch sizes between
              # these two checks.
              false_fail_rate=1e-7,
              false_pass_rate=1e-6,
          ),
          # 4% relative error
          0.08,
      )
      self.evaluate([check1, check2])
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import spherical_uniform
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 6 for calling the _SphericalUniformTest obj's underlying member method code with example usage: obj.VerifyMean(dim) without return types