code: def forward(self, x):
      x = self.features(x)
      x = x.view(-1, 512 * 4 * 4)
      x = self.classifier(x)
      return x
  
imports: from typing import Callable, Union, List
  import time
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.optim import Optimizer
  from torch.utils.data import DataLoader
  from torchvision import datasets, transforms
  import nni
  from nni.compression.quantization import BNNQuantizer
  from nni.compression.utils import TorchEvaluator
  from nni.common.types import SCHEDULER
label_desc: Use image node_id 2 for calling the VGG_Cifar10 obj's underlying member method code with example usage: obj.forward(x) and returns: x