code: def __init__(
      self,
      cardinalities: List[int],
      embedding_dims: List[int],
  ) -> None:
      super().__init__()
  
      self.__num_features = len(cardinalities)
  
      def create_embedding(c: int, d: int) -> nn.Embedding:
          embedding = nn.Embedding(c, d)
          return embedding
  
      self.__embedders = nn.ModuleList(
          [
              create_embedding(c, d)
              for c, d in zip(cardinalities, embedding_dims)
          ]
      )
  
file_path: gluonts/src/gluonts/nursery/robust-mts-attack/pts/modules/feature.py
imports: from typing import List, Optional
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new FeatureEmbedder object from inherited base classes: nn with example: obj = FeatureEmbedder(cardinalities, embedding_dims)