code: def create_q_network(num_actions):
      """Create a Q network following the architecture from Minh 15."""
  
      kernel_initializer = tf.keras.initializers.VarianceScaling(
          scale=2.0
      )
      conv2d = functools.partial(
          tf.keras.layers.Conv2D,
          activation=tf.keras.activations.relu,
          kernel_initializer=kernel_initializer,
      )
      dense = functools.partial(
          tf.keras.layers.Dense,
          activation=tf.keras.activations.relu,
          kernel_initializer=kernel_initializer,
      )
      logits = functools.partial(
          tf.keras.layers.Dense,
          activation=None,
          kernel_initializer=kernel_initializer,
      )
  
      return sequential.Sequential(
          # We divide the grayscale pixel values by 255 here rather than storing
          # normalized values because uint8s are 4x cheaper to store than float32s.
          [
              tf.keras.layers.Lambda(lambda x: x / 255),
              conv2d(32, (8, 8), 4),
              conv2d(64, (4, 4), 2),
              conv2d(64, (3, 3), 1),
              tf.keras.layers.Flatten(),
              dense(512),
              logits(num_actions),
          ]
      )
  
imports: import functools
  import os
  from absl import app
  from absl import flags
  from absl import logging
  import gin
  import reverb
  import tensorflow.compat.v2
  from tf_agents.agents.dqn import dqn_agent
  from tf_agents.environments import suite_atari
  from tf_agents.metrics import py_metrics
  from tf_agents.networks import sequential
  from tf_agents.policies import py_tf_eager_policy
  from tf_agents.policies import random_py_policy
  from tf_agents.replay_buffers import reverb_replay_buffer
  from tf_agents.replay_buffers import reverb_utils
  from tf_agents.system import system_multiprocessing
  from tf_agents.train import actor
  from tf_agents.train import learner
  from tf_agents.train import triggers
  from tf_agents.train.utils import spec_utils
  from tf_agents.train.utils import train_utils
  from tf_agents.utils import common
label_desc: Use image node_id 1 for calling a global function with example usage: create_q_network(num_actions) and returns: sequential