code: def create_mlp(
      input_shape: Tuple[int], n_actions: int, hidden_size: int = 128
  ):
      """Simple Multi-Layer Perceptron network."""
      return nn.Sequential(
          nn.Linear(input_shape[0], hidden_size),
          nn.ReLU(),
          nn.Linear(hidden_size, hidden_size),
          nn.ReLU(),
          nn.Linear(hidden_size, n_actions),
      )
  
imports: import argparse
  from typing import Callable, Iterator, List, Tuple
  import gym
  import torch
  from lightning.pytorch import LightningModule, Trainer, cli_lightning_logo, seed_everything
  from torch import nn
  from torch.distributions import Categorical, Normal
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader, IterableDataset
label_desc: Use image node_id 1 for calling a global function with example usage: create_mlp(input_shape, n_actions, hidden_size) and returns: nn