code: def forward(self, features: torch.Tensor) -> List[torch.Tensor]:
      if self.__num_features > 1:
          real_feature_slices = torch.tensor_split(
              features, self.feature_slices[1:], dim=-1
          )
      else:
          real_feature_slices = [features]
  
      return [
          proj(real_feature_slice)
          for proj, real_feature_slice in zip(
              self._projector, real_feature_slices
          )
      ]
  
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 2 for calling the FeatureProjector obj's underlying member method code with example usage: obj.forward(features) and returns: unknown