class_docstr: Noisy Network from Fortunato et al. (2018).
  
  Attributes:
    rng_key: jax.interpreters.xla.DeviceArray, key for JAX RNG.
    eval_mode: bool, whether to turn off noise during evaluation.
code: def sample_noise(key, shape):
      return jax.random.normal(key, shape)
  
imports: import itertools
  import time
  from typing import Optional, Sequence, Tuple, Union
  from absl import logging
  from dopamine.discrete_domains import atari_lib
  from flax import linen
  import gin
  import jax
  import jax.numpy
  import numpy
label_desc: Use image node_id 1 for calling the NoisyNetwork obj's underlying member method code with example usage: obj.sample_noise(key, shape) and returns: jax