class_docstr: Basic DQN Model.
  
  >>> DQNLightning(env="CartPole-v1")  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
  DQNLightning(
    (net): DQN(
      (net): Sequential(...)
    )
    (target_net): DQN(
      (net): Sequential(...)
    )
  )
docstr: Get train loader.
docstr_tok: ["Get","train","loader","."]
code: def train_dataloader(self) -> DataLoader:
      """Get train loader."""
      return self.__dataloader()
  
imports: import argparse
  from collections import OrderedDict, deque, namedtuple
  from typing import Iterator, List, Tuple
  import gym
  import numpy
  import torch
  import torch.nn
  import torch.optim
  from lightning.pytorch import LightningModule, Trainer, cli_lightning_logo, seed_everything
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader
  from torch.utils.data.dataset import IterableDataset
label_desc: Use image node_id 8 for calling the DQNLightning obj's underlying member method code with example usage: obj.train_dataloader() and returns: self