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.
code: def _get_input_label_from_iter(self, batch_data):
      input_feat = [
          batch_data["user_index_batch"],
          batch_data["clicked_title_batch"],
          batch_data["candidate_title_batch"],
      ]
      input_label = batch_data["labels"]
      return input_feat, input_label
  
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 2 for calling the NPAModel obj's underlying member method code with example usage: obj._get_input_label_from_iter(batch_data) and returns: input_feat,  input_label