code: def forward(self, features: torch.Tensor) -> List[torch.Tensor]:  # type: ignore
      concat_features = super().forward(features=features)
  
      if self._num_features > 1:
          return torch.chunk(
              concat_features, self._num_features, dim=-1
          )
      else:
          return [concat_features]
  
imports: from typing import List, Optional, Tuple
  import torch
  import torch.nn
  from gluonts.core.component import validated
  from gluonts.torch.modules.feature 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: torch, list