code: def forward(self, x):
      x = self.conv1(x)
      x = F.relu(x)
      x = self.conv2(x)
      x = F.relu(x)
      x = F.max_pool2d(x, 2)
      x = self.dropout1(x)
      x = torch.flatten(x, 1)
      x = self.fc1(x)
      x = F.relu(x)
      x = self.dropout2(x)
      x = self.fc2(x)
      output = F.log_softmax(x, dim=1)
      return output
  
imports: import sys
  import torch
  import torchvision.transforms
  from torch.nn import functional
  import torch.nn
  from torchmetrics import Accuracy
  from torchvision.datasets.mnist import MNIST
  from pytorch_lightning import LightningModule
  from clearml import Task
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: output