class_docstr: LSTUR model(Neural News Recommendation with Multi-Head Self-Attention)
  
  Mingxiao An, Fangzhao Wu, Chuhan Wu, Kun Zhang, Zheng Liu and Xing Xie:
  Neural News Recommendation with Long- and Short-term User Representations, ACL 2019
  
  Attributes:
      word2vec_embedding (numpy.ndarray): Pretrained word embedding matrix.
      hparam (object): Global hyper-parameters.
docstr: Build LSTUR model and scorer.
  
  Returns:
      object: a model used to train.
      object: a model used to evaluate and inference.
docstr_tok: ["Build","LSTUR","model","and","scorer",".","Returns",":","object",":","a","model","used","to","train",".","object",":","a","model","used","to","evaluate","and","inference","."]
code: def _build_graph(self):
      """Build LSTUR model and scorer.
  
      Returns:
          object: a model used to train.
          object: a model used to evaluate and inference.
      """
  
      model, scorer = self._build_lstur()
      return model, scorer
  
file_path: recommenders/recommenders/models/newsrec/models/lstur.py
imports: import tensorflow.compat.v1.keras
  from tensorflow.compat.v1.keras import layers
  from recommenders.models.newsrec.models.base_model import BaseModel
  from recommenders.models.newsrec.models.layers import AttLayer2, ComputeMasking, OverwriteMasking
label_desc: Use image node_id 5 for calling the LSTURModel obj's underlying member method code with example usage: obj._build_graph() and returns: model,  scorer