code: def testPmfUniform(self):
      # Check that distribution with equal scores gives uniform probability.
      scores = self._rng.uniform() * np.ones(
          shape=(8, 2, 10), dtype=np.float32
      )
      dist = plackett_luce.PlackettLuce(
          scores=scores, validate_args=True
      )
      np_sample = self.evaluate(dist.sample(seed=test_util.test_seed()))
      np_prob = self.evaluate(dist.log_prob(np_sample))
      n_fac = scipy.special.factorial(scores.shape[-1]).astype(
          np.float32
      )
      expected_prob = self.evaluate(
          -tf.math.log(n_fac) * tf.ones_like(np_prob)
      )
      self.assertAllClose(np_prob, expected_prob)
  
imports: import numpy
  import scipy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import plackett_luce
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 7 for calling the PlackettLuceTest obj's underlying member method code with example usage: obj.testPmfUniform() without return types