code: def forward(self, x):
      x = self.pool(F.relu(self.conv1(x)))
      x = self.pool(F.relu(self.conv2(x)))
      x = torch.flatten(x, 1)  # flatten all dimensions except batch
      x = F.relu(self.fc1(x))
      x = F.relu(self.fc2(x))
      x = self.fc3(x)
      return x
  
file_path: pytorch-lightning/tests/parity_fabric/models.py
imports: from abc import ABC, abstractmethod
  from typing import Callable
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.optim import Optimizer
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 2 for calling the ConvNet obj's underlying member method code with example usage: obj.forward(x) and returns: x