code: def embedding_layer(self, item_seq):
      position_ids = torch.arange(
          item_seq.size(1), dtype=torch.long, device=item_seq.device
      )
      position_embedding = self.position_embedding(position_ids)
      item_emb = self.item_embedding(item_seq)
      return item_emb, position_embedding
  
file_path: RecBole/recbole/model/sequential_recommender/lightsans.py
imports: import torch
  from torch import nn
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.loss import BPRLoss
  from recbole.model.layers import LightTransformerEncoder
label_desc: Use image node_id 3 for calling the LightSANs obj's underlying member method code with example usage: obj.embedding_layer(item_seq) and returns: item_emb,  position_embedding