class_docstr: Actual model code for the Transresnet Agent.
docstr: Encode image features.
  
  :param image_features:
      list of image features
  
  :return:
      encoded representation of the image features
docstr_tok: ["Encode","image","features",".",":","param","image_features",":","list","of","image","features",":","return",":","encoded","representation","of","the","image","features"]
code: def forward_image(self, image_features):
      """
      Encode image features.
  
      :param image_features:
          list of image features
  
      :return:
          encoded representation of the image features
      """
      img_encoded = None
      if image_features is not None:
          stacked = torch.stack(image_features)
          if self.use_cuda:
              stacked = stacked.cuda()
          img_encoded = self.image_encoder(stacked)
  
      return img_encoded
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  import torch
  from torch import nn
  from torch import optim
  from parlai.agents.transformer.modules import TransformerEncoder
  from parlai.agents.transformer import transformer
  from parlai.utils.io import PathManager
label_desc: Use image node_id 9 for calling the TransresnetModel obj's underlying member method code with example usage: obj.forward_image(image_features) and returns: img_encoded