code: def VerifyEntropy(self, dim):
      seed_stream = test_util.test_seed_stream()
      mean_direction = tf.random.uniform(
          shape=[5, dim], minval=1.0, maxval=2.0, seed=seed_stream()
      )
      mean_direction = tf.nn.l2_normalize(mean_direction, axis=-1)
      concentration = tf.math.log(
          tf.random.uniform(
              shape=[2, 1], minval=1.0, maxval=100.0, seed=seed_stream()
          )
      )
      vmf = von_mises_fisher.VonMisesFisher(
          mean_direction=mean_direction,
          concentration=concentration,
          validate_args=True,
          allow_nan_stats=False,
      )
      samples = vmf.sample(int(3e4), seed=test_util.test_seed())
      entropy_samples = -vmf.log_prob(samples)
      true_entropy, entropy_samples = self.evaluate(
          [vmf.entropy(), entropy_samples]
      )
      self.assertAllMeansClose(
          entropy_samples, true_entropy, axis=0, rtol=3e-2
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import spherical_uniform
  from tensorflow_probability.python.distributions import von_mises_fisher
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 11 for calling the VonMisesFisherTest obj's underlying member method code with example usage: obj.VerifyEntropy(dim) without return types