class_docstr: A recurrent network for use with IMPALA.
  
  See https://arxiv.org/pdf/1802.01561.pdf for more information.
code: def initial_state(
      self, batch_size: Optional[int], **unused_kwargs
  ) -> hk.LSTMState:
      return self._core.initial_state(batch_size)
  
imports: from typing import Any, Optional, Sequence, Tuple
  from acme.jax.networks import base
  from acme.jax.networks import duelling
  from acme.jax.networks import embedding
  from acme.jax.networks import policy_value
  from acme.jax.networks import resnet
  from acme.wrappers import observation_action_reward
  import haiku
  import jax
  import jax.numpy
label_desc: Use image node_id 3 for calling the DeepIMPALAAtariNetwork obj's underlying member method code with example usage: obj.initial_state(batch_size) and returns: self