code: def __init__(self):
      super().__init__()
      self.layer = Sequential(
          OrderedDict(
              [
                  ("mlp_1", nn.Linear(32, 32)),
                  ("mlp_2", nn.Linear(32, 32, bias=False)),
                  ("mlp_3", nn.Linear(32, 2)),
              ]
          )
      )
  
imports: import re
  from collections import OrderedDict
  from logging import INFO
  from typing import Union
  import pytest
  import torch
  import torch.nn.utils.prune
  from lightning.pytorch import Trainer, seed_everything
  from lightning.pytorch.callbacks import ModelCheckpoint, ModelPruning
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch import nn
  from torch.nn import Sequential
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 1 to create a new TestModel object from inherited base classes: BoringModel with example: obj = TestModel()