class_docstr: Jax DQN network for classic control environments.
code: def __call__(self, x):
      if not self.inputs_preprocessed:
          x = x.astype(jnp.float32)
          x = x.reshape((-1))  # flatten
          if self.min_vals is not None:
              x -= self._min_vals
              x /= self._max_vals - self._min_vals
              x = 2.0 * x - 1.0  # Rescale in range [-1, 1].
      for layer in self.layers:
          x = layer(x)
          x = nn.relu(x)
      q_values = self.final_layer(x)
      return atari_lib.DQNNetworkType(q_values)
  
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 2 for calling the ClassicControlDQNNetwork obj's underlying member method code with example usage: obj.__call__(x) and returns: atari_lib