code: def __init__(self, l1=120, l2=84):
      super(Net, self).__init__()
      self.conv1 = nn.Conv2d(3, 6, 5)
      self.pool = nn.MaxPool2d(2, 2)
      self.conv2 = nn.Conv2d(6, 16, 5)
      self.fc1 = nn.Linear(16 * 5 * 5, l1)
      self.fc2 = nn.Linear(l1, l2)
      self.fc3 = nn.Linear(l2, 10)
  
imports: import numpy
  import os
  import tempfile
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from filelock import FileLock
  from torch.utils.data import random_split
  import torchvision
  import torchvision.transforms
  from typing import Dict
  import ray
  from ray import train, tune
  from ray.train import Checkpoint
  from ray.tune.schedulers import ASHAScheduler
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net(l1, l2)