class_docstr: Gets a list of arguments and pass them as separate arguments.
  
  Example
  ```
    class Critic(snt.RNNCore):
      def __call__(self, o, a, prev_state):
        pass
  
    critic = Critic()
    RNNUnpackWrapper(critic)((o, a), prev_state)
  ```
  calls m(o, a, prev_state)
class_docstr_tok: ["Gets","a","list","of","arguments","and","pass","them","as","separate","arguments",".","Example","``","`","class","Critic","(","snt.RNNCore",")",":","def","__call__","(","self",",","o",",","a",",","prev_state",")",":","pass","critic","=","Critic","(",")","RNNUnpackWrapper","(","critic",")","(","(","o",",","a",")",",","prev_state",")","``","`","calls","m","(","o",",","a",",","prev_state",")"]
code: def __init__(
      self, module: snt.RNNCore, name: str = "RNNUnpackWrapper"
  ):
      super().__init__(name=name)
      self._module = module
  
imports: import functools
  from typing import NamedTuple, Optional, Sequence, Tuple
  from absl import logging
  from acme import types
  from acme.tf import savers
  from acme.tf import utils
  from acme.tf.networks import base
  import sonnet
  import tensorflow
  import tensorflow_probability
  import tree
label_desc: Use image node_id 1 to create a new RNNUnpackWrapper object from inherited base classes: snt with example: obj = RNNUnpackWrapper(module, name)