class_docstr: A recurrent network for use with IMPALA.
  
  See https://arxiv.org/pdf/1802.01561.pdf for more information.
class_docstr_tok: ["A","recurrent","network","for","use","with","IMPALA",".","See","https",":","\/\/arxiv.org\/pdf\/1802.01561.pdf","for","more","information","."]
code: def __init__(self, num_actions: int):
      super().__init__(name="impala_atari_network")
      self._embed = embedding.OAREmbedding(
          torso=AtariTorso(), num_actions=num_actions
      )
      self._core = snt.LSTM(256)
      self._head = snt.Sequential(
          [
              snt.Linear(256),
              tf.nn.relu,
              policy_value.PolicyValueHead(num_actions),
          ]
      )
      self._num_actions = num_actions
  
imports: from typing import Optional, Tuple
  from acme.tf.networks import base
  from acme.tf.networks import duelling
  from acme.tf.networks import embedding
  from acme.tf.networks import policy_value
  from acme.tf.networks import recurrence
  from acme.tf.networks import vision
  from acme.wrappers import observation_action_reward
  import sonnet
  import tensorflow
label_desc: Use image node_id 1 to create a new IMPALAAtariNetwork object from inherited base classes: snt with example: obj = IMPALAAtariNetwork(num_actions)