class_docstr: Shallow models for knowledge representation learning.
      
code: def _get_ent_embedding(self, index):
      emb = self.ent_embedding(index)
      if self._use_feat:
          feat = paddle.to_tensor(
              self._ent_feat[index.numpy()].astype("float32")
          )
          emb = self.trans_ent(feat, emb)
      return emb
  
imports: import os
  import json
  import math
  import warnings
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from pgl.utils.shared_embedding import SharedEmbedding
  from models.score_funcs import TransEScore, RotatEScore, DistMultScore, ComplExScore, QuatEScore, OTEScore
  from models.init_func import InitFunction
  from utils import uniform, timer_wrapper
label_desc: Use image node_id 16 for calling the KGEModel obj's underlying member method code with example usage: obj._get_ent_embedding(index) and returns: emb