class_docstr: Noisy Network from Fortunato et al. (2018).
code: def f(x):
      # See (10) and (11) in Fortunato et al. (2018).
      return jnp.multiply(jnp.sign(x), jnp.power(jnp.abs(x), 0.5))
  
imports: import collections
  import functools
  import time
  from typing import Any, Callable, Optional, Tuple
  from dopamine.jax.networks import preprocess_atari_inputs
  from flax import linen
  import gin
  import jax
  from jax import lax
  from jax import random
  from jax.nn import initializers
  import jax.numpy
  import numpy
label_desc: Use image node_id 2 for calling the NoisyNetwork obj's underlying member method code with example usage: obj.f(x) and returns: jnp