class_docstr: Class used to handle agent-side observation stacking.
  
  Once an ObservationStacker is initialized and an initial_state is obtained
  from it, one can stack nested observations by simply calling the
  ObservationStacker and passing it the new observation and current state of its
  observation stack.
  
  See also observation_stacking.wrap_actor_core for hints on how to use it.
code: def initial_state(self) -> StackerState:
      return StackerState(
          stack=self._zero_stack, needs_reset=jnp.array(True)
      )
  
imports: from typing import Any, Mapping, NamedTuple, Tuple
  from acme import specs
  from acme import types
  from acme.agents.jax import actor_core
  from acme.jax import networks
  from acme.jax import types
  from acme.jax import utils
  from acme.tf import utils
  import jax
  import jax.numpy
  import reverb
  import tensorflow
  import tree
label_desc: Use image node_id 3 for calling the ObservationStacker obj's underlying member method code with example usage: obj.initial_state() and returns: StackerState