code: def forward(self, x):
      x = x.view(-1, 784)
      hidden = self.relu(self.fc1(x))
      hidden = self.relu(self.fc2(hidden))
      y = torch.sigmoid(self.fc3(hidden))
      return y
  
file_path: pyro/examples/cvae/baseline.py
imports: import copy
  from pathlib import Path
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from tqdm import tqdm
label_desc: Use image node_id 2 for calling the BaselineNet obj's underlying member method code with example usage: obj.forward(x) and returns: y