class_docstr: References:
  ===========
      - https://towardsdatascience.com/deep-reinforcement-learning-build-a-deep-q-network-dqn-to-play-cartpole-with-tensorflow-2-and-gym-8e105744b998
      - https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html#dqn-algorithm
      - https://arxiv.org/abs/1802.00308
code: def restore(self, path: str, **kwargs):
      self.policy_network = tf.keras.models.load_model(path)
      self.target_network = tf.keras.models.clone_model(
          self.policy_network
      )
      self.target_network.trainable = False
  
file_path: tensortrade/tensortrade/agents/dqn_agent.py
imports: from deprecated import deprecated
  import random
  import numpy
  import tensorflow
  from collections import namedtuple
  from tensortrade.agents import Agent, ReplayMemory
  from datetime import datetime
label_desc: Use image node_id 3 for calling the DQNAgent obj's underlying member method code with example usage: obj.restore(path) without return types