class_docstr: Identical to PlackettLuce, with input signature modified to our needs.
docstr: Initializes an instance of NoPenaltyPlackettLuce.
  
  Args:
    features: Unused for this distribution.
    num_slots: The number of slots to fill: this many items will be sampled.
    logits: Unnormalized log probabilities for the PlackettLuce distribution.
      Shape is `[num_items]`.
    penalty_mixture_coefficient: Unused for this distribution.
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code: def __init__(
      self,
      features: types.Tensor,
      num_slots: int,
      logits: types.Tensor,
      penalty_mixture_coefficient: float = 1.0,
  ):
      """Initializes an instance of NoPenaltyPlackettLuce.
  
      Args:
        features: Unused for this distribution.
        num_slots: The number of slots to fill: this many items will be sampled.
        logits: Unnormalized log probabilities for the PlackettLuce distribution.
          Shape is `[num_items]`.
        penalty_mixture_coefficient: Unused for this distribution.
      """
      self._num_slots = num_slots
      super(NoPenaltyPlackettLuce, self).__init__(
          scores=tf.math.exp(logits)
      )
  
imports: from typing import Optional, Sequence, Text
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import tf_policy
  from tf_agents.policies import utils
  from tf_agents.specs import bandit_spec_utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.typing import types
label_desc: Use image node_id 1 to create a new NoPenaltyPlackettLuce object from inherited base classes: tfd with example: obj = NoPenaltyPlackettLuce(features, num_slots, logits, penalty_mixture_coefficient)