code: def __init__(self):
      super(ConvNet, self).__init__()
      self.conv1 = nn.Conv2d(1, 3, kernel_size=3)
      self.fc = nn.Linear(192, 10)
  
file_path: ray/doc/source/tune/doc_code/pytorch_optuna.py
imports: import os
  from filelock import FileLock
  import torch.nn
  import torch.nn.functional
  from torchvision import datasets, transforms
  import torch
  from ray import train, tune
  from ray.tune.search.optuna import OptunaSearch
label_desc: Use image node_id 1 to create a new ConvNet object from inherited base classes: nn with example: obj = ConvNet()