code: def forward(self, features: torch.Tensor) -> List[torch.Tensor]:
      concat_features = super(FeatureEmbedder, self).forward(
          features=features
      )
  
      if self.__num_features > 1:
          features = torch.chunk(
              concat_features, self.__num_features, dim=-1
          )
      else:
          features = [concat_features]
  
      return features
  
imports: from typing import List, Optional, Tuple
  import numpy
  import torch
  import torch.nn
  from pts.modules import FeatureEmbedder
label_desc: Use image node_id 1 for calling the FeatureEmbedder obj's underlying member method code with example usage: obj.forward(features) and returns: features