docstr: Extract feature vectors from input images.
docstr_tok: ["Extract","feature","vectors","from","input","images","."]
code: def forward(self, images):
      """Extract feature vectors from input images."""
      with torch.no_grad():
          features = self.resnet(images)
      features = features.reshape(features.size(0), -1)
      features = self.bn(self.linear(features))
      return features
  
file_path: pytorch-tutorial/tutorials/03-advanced/image_captioning/model.py
imports: import torch
  import torch.nn
  import torchvision.models
  from torch.nn.utils.rnn import pack_padded_sequence
label_desc: Use image node_id 2 for calling the EncoderCNN obj's underlying member method code with example usage: obj.forward(images) and returns: features