code: def __init__(self):
      super().__init__()
      self.conv1 = nn.Conv2d(1, 16, 8, 2, padding=3)
      self.conv2 = nn.Conv2d(16, 32, 4, 2)
      self.fc1 = nn.Linear(32 * 4 * 4, 32)
      self.fc2 = nn.Linear(32, 10)
  
file_path: opacus/examples/mnist.py
imports: import argparse
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from opacus import PrivacyEngine
  from torchvision import datasets, transforms
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new SampleConvNet object from inherited base classes: nn with example: obj = SampleConvNet()