class_docstr: Network head that produces a categorical distribution and value.
class_docstr_tok: ["Network","head","that","produces","a","categorical","distribution","and","value","."]
code: def __init__(
      self,
      num_values: int,
      name: Optional[str] = None,
  ):
      super().__init__(name=name)
      self._logit_layer = hk.Linear(num_values)
      self._value_layer = hk.Linear(1)
  
imports: from typing import Any, List, Optional, Sequence, Union, Callable
  import chex
  import haiku
  import jax
  import jax.numpy
  import numpy
  import tensorflow_probability
  import tensorflow_probability.substrates.jax
label_desc: Use image node_id 1 to create a new CategoricalValueHead object from inherited base classes: hk with example: obj = CategoricalValueHead(num_values, name)