code: def __init__(self, hidden_size):
      super(Net, self).__init__()
      self.conv1 = nn.Conv2d(1, 20, 5, 1)
      self.conv2 = nn.Conv2d(20, 50, 5, 1)
      self.fc1 = nn.Linear(4 * 4 * 50, hidden_size)
      self.fc2 = nn.Linear(hidden_size, 10)
  
file_path: nni/examples/trials/mnist-pytorch/mnist_tensorboard.py
imports: import os
  import argparse
  import logging
  import nni
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torch.utils.tensorboard import SummaryWriter
  from nni.utils import merge_parameter
  from torchvision import datasets, transforms
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net(hidden_size)