code: def forward(self, x):
      x = F.relu(F.max_pool2d(self.conv1(x), 2))
      x = F.relu(F.max_pool2d(self.conv2(x), 2))
      x = x.view(-1, 1600)
      x = F.relu(self.fc1(x))
      x = F.dropout(x, training=self.training)
      x = self.fc2(x)
      return F.log_softmax(x), F.log_softmax(x)
  
file_path: pywick/tests/integration/fit_loader_simple/single_input_multi_target.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader
  from pywick.modules import ModuleTrainer
  from pywick.datasets.TensorDataset import TensorDataset
  import os
  from torchvision import datasets
label_desc: Use image node_id 2 for calling the Network obj's underlying member method code with example usage: obj.forward(x) and returns: F,  F