code: def forward(self, x):
      out = self.layer1(x)
      out = self.layer2(out)
      out = out.reshape(out.size(0), -1)
      out = self.fc(out)
      return out
  
file_path: aim/examples/pytorch_track_images.py
imports: import logging
  import torch
  import torch.nn
  import torchvision
  import torchvision.transforms
  from aim import Run
  from aim.sdk.objects.image import convert_to_aim_image_list
  from tqdm import tqdm
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: out