code: def __init__(self) -> None:
      super().__init__()
      self.conv1 = nn.Conv2d(1, 32, 3, 1)
      self.conv2 = nn.Conv2d(32, 64, 3, 1)
      self.dropout1 = nn.Dropout(0.25)
      self.dropout2 = nn.Dropout(0.5)
      self.fc1 = nn.Linear(9216, 128)
      self.fc2 = nn.Linear(128, 10)
  
file_path: pytorch-lightning/examples/fabric/image_classifier/train_fabric.py
imports: import argparse
  from os import path
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torchvision.transforms
  from lightning.fabric import Fabric, seed_everything
  from torch.optim.lr_scheduler import StepLR
  from torchmetrics.classification import Accuracy
  from torchvision.datasets import MNIST
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net()