class_docstr: Iterable Dataset containing the ExperienceBuffer which will be updated with new experiences during training.
  
  >>> RLDataset(ReplayBuffer(5))  # doctest: +ELLIPSIS
  <...reinforce_learn_Qnet.RLDataset object at ...>
code: def __iter__(self) -> Iterator:
      states, actions, rewards, dones, new_states = self.buffer.sample(
          self.sample_size
      )
      for i in range(len(dones)):
          yield states[i], actions[i], rewards[i], dones[i], new_states[
              i
          ]
  
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 2 for calling the RLDataset obj's underlying member method code with example usage: obj.__iter__() without return types