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 __call__(
      self, inputs: observation_action_reward.OAR, state: snt.LSTMState
  ) -> Tuple[Tuple[Logits, Value], snt.LSTMState]:
      embeddings = self._embed(inputs)
      embeddings, new_state = self._core(embeddings, state)
      logits, value = self._head(embeddings)  # [B, A]
  
      return (logits, value), new_state
  
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 2 for calling the IMPALAAtariNetwork obj's underlying member method code with example usage: obj.__call__(inputs, state) and returns: logits,  value,  new_state