class_docstr: NPA model(Neural News Recommendation with Attentive Multi-View Learning)
  
  Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang and Xing Xie:
  NPA: Neural News Recommendation with Personalized Attention, KDD 2019, ADS track.
  
  Attributes:
      word2vec_embedding (numpy.ndarray): Pretrained word embedding matrix.
      hparam (object): Global hyper-parameters.
docstr: Build NPA model and scorer.
  
  Returns:
      object: a model used to train.
      object: a model used to evaluate and inference.
code: def _build_graph(self):
      """Build NPA model and scorer.
  
      Returns:
          object: a model used to train.
          object: a model used to evaluate and inference.
      """
  
      model, scorer = self._build_npa()
      return model, scorer
  
file_path: recommenders/recommenders/models/newsrec/models/npa.py
imports: import tensorflow.keras
  from tensorflow.keras import layers
  from recommenders.models.newsrec.models.base_model import BaseModel
  from recommenders.models.newsrec.models.layers import PersonalizedAttentivePooling
label_desc: Use image node_id 3 for calling the NPAModel obj's underlying member method code with example usage: obj._build_graph() and returns: model,  scorer