code: def forward(self, x):
      batch_size, channels, height, width = x.size()
  
      # (b, 1, 28, 28) -> (b, 1*28*28)
      x = x.view(batch_size, -1)
      x = self.layer_1(x)
      x = F.relu(x)
      x = self.layer_2(x)
      x = F.relu(x)
      x = self.layer_3(x)
  
      x = F.log_softmax(x, dim=1)
      return x
  
file_path: guildai/examples/pytorch-lightning/mnist.py
imports: import os
  import argparse
  import torch
  from torch import nn
  from torch.nn import functional
  from torch.optim import Adam
  from torch.utils.data import DataLoader, random_split
  from torchvision import datasets, transforms
  from torchvision.datasets import MNIST
  from pytorch_lightning import Trainer
  from pytorch_lightning.core.lightning import LightningModule
label_desc: Use image node_id 2 for calling the LitMNIST obj's underlying member method code with example usage: obj.forward(x) and returns: x