code: def __init__(self):
      super(NeuralNetwork, self).__init__()
      self.flatten = nn.Flatten()
      self.linear_relu_stack = nn.Sequential(
          nn.Linear(28 * 28, params["features"]),
          nn.ReLU(),
          nn.Linear(params["features"], params["features"]),
          nn.ReLU(),
          nn.Linear(params["features"], 10),
      )
  
file_path: nni/examples/tutorials/hpo_quickstart_pytorch/model.py
imports: import nni
  import torch
  from torch import nn
  from torch.utils.data import DataLoader
  from torchvision import datasets
  from torchvision.transforms import ToTensor
label_desc: Use image node_id 1 to create a new NeuralNetwork object from inherited base classes: nn with example: obj = NeuralNetwork()