docstr: Extract multiple convolutional feature maps.
docstr_tok: ["Extract","multiple","convolutional","feature","maps","."]
code: def forward(self, x):
      """Extract multiple convolutional feature maps."""
      features = []
      for name, layer in self.vgg._modules.items():
          x = layer(x)
          if name in self.select:
              features.append(x)
      return features
  
file_path: pytorch-tutorial/tutorials/03-advanced/neural_style_transfer/main.py
imports: from __future__ import division
  from torchvision import models
  from torchvision import transforms
  from PIL import Image
  import argparse
  import torch
  import torchvision
  import torch.nn
  import numpy
label_desc: Use image node_id 2 for calling the VGGNet obj's underlying member method code with example usage: obj.forward(x) and returns: features