code: def __init__(self):
      super().__init__()
      self.flatten = nn.Flatten()
      self.linear_relu_stack = nn.Sequential(
          *chain(
              [nn.Linear(28 * 28, layer_size), nn.ReLU()],
              *[
                  [nn.Linear(layer_size, layer_size), nn.ReLU()]
                  for _ in range(layer_count)
              ],
              [nn.Linear(layer_size, 10)],
          )
      )
  
file_path: guildai/examples/pytorch-quickstart/train.py
imports: from binascii import crc32
  from itertools import chain
  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()