class_docstr: Patch Description Network medium
  
  Args:
      out_channels (int): number of convolution output channels
code: def forward(self, x):
      x = imagenet_norm_batch(x)
      x = F.relu(self.conv1(x))
      x = self.avgpool1(x)
      x = F.relu(self.conv2(x))
      x = self.avgpool2(x)
      x = F.relu(self.conv3(x))
      x = F.relu(self.conv4(x))
      x = F.relu(self.conv5(x))
      x = self.conv6(x)
      return x
  
imports: from __future__ import annotations
  import logging
  import random
  from enum import Enum
  import torch
  import torch.nn.functional
  from torch import Tensor, nn
  from torchvision import transforms
label_desc: Use image node_id 2 for calling the PDN_M obj's underlying member method code with example usage: obj.forward(x) and returns: x