code: def forward(self, x):
      x = F.relu(F.max_pool2d(self.conv1(x), 2))
      x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
      x = x.view(-1, 320)
      x = F.relu(self.fc1(x))
      x = F.dropout(x, training=self.training)
      x = self.fc2(x)
      return F.log_softmax(x, dim=1)
  
imports: import unittest
  import torch
  import torch.nn.functional
  import torchvision
  import nni.nas.nn.pytorch.layers
  from nni.nas.nn.pytorch import ParametrizedModule
  from .convert_mixin import ConvertMixin, ConvertWithShapeMixin
label_desc: Use image node_id 2 for calling the MnistNet obj's underlying member method code with example usage: obj.forward(x) and returns: F