code: def __init__(self):
      super(Net, self).__init__()
      self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
      self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
      self.conv2_drop = nn.Dropout2d()
      self.fc1 = nn.Linear(320, 50)
      self.fc2 = nn.Linear(50, 10)
  
file_path: horovod/examples/pytorch/pytorch_mnist.py
imports: import argparse
  import os
  from packaging import version
  import torch.multiprocessing
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torch.utils.data.distributed
  from filelock import FileLock
  from torchvision import datasets, transforms
  import horovod
  import horovod.torch
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net()