code: def testFloatingSamples(self):
      scores = np.array([[[0.1, 2.3, 5.0], [4.2, 0.5, 3.1]]])
      dist = plackett_luce.PlackettLuce(
          scores, dtype=tf.float64, validate_args=True
      )
      # Expect no errors from computing log_prob of a sample.
      self.evaluate(
          dist.log_prob(dist.sample(seed=test_util.test_seed()))
      )
  
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 11 for calling the PlackettLuceTest obj's underlying member method code with example usage: obj.testFloatingSamples() without return types