class_docstr: NRMS model(Neural News Recommendation with Multi-Head Self-Attention)
  
  Chuhan Wu, Fangzhao Wu, Suyu Ge, Tao Qi, Yongfeng Huang,and Xing Xie, "Neural News
  Recommendation with Multi-Head Self-Attention" in Proceedings of the 2019 Conference
  on Empirical Methods in Natural Language Processing and the 9th International Joint Conference
  on Natural Language Processing (EMNLP-IJCNLP)
  
  Attributes:
      word2vec_embedding (numpy.ndarray): Pretrained word embedding matrix.
      hparam (object): Global hyper-parameters.
docstr: Initialization steps for NRMS.
  Compared with the BaseModel, NRMS need word embedding.
  After creating word embedding matrix, BaseModel's __init__ method will be called.
  
  Args:
      hparams (object): Global hyper-parameters. Some key setttings such as head_num and head_dim are there.
      iterator_creator_train (object): NRMS data loader class for train data.
      iterator_creator_test (object): NRMS data loader class for test and validation data
docstr_tok: ["Initialization","steps","for","NRMS",".","Compared","with","the","BaseModel",",","NRMS","need","word","embedding",".","After","creating","word","embedding","matrix",",","BaseModel","'s","__init__","method","will","be","called",".","Args",":","hparams","(","object",")",":","Global","hyper-parameters",".","Some","key","setttings","such","as","head_num","and","head_dim","are","there",".","iterator_creator_train","(","object",")",":","NRMS","data","loader","class","for","train","data",".","iterator_creator_test","(","object",")",":","NRMS","data","loader","class","for","test","and","validation","data"]
code: def __init__(
      self,
      hparams,
      iterator_creator,
      seed=None,
  ):
      """Initialization steps for NRMS.
      Compared with the BaseModel, NRMS need word embedding.
      After creating word embedding matrix, BaseModel's __init__ method will be called.
  
      Args:
          hparams (object): Global hyper-parameters. Some key setttings such as head_num and head_dim are there.
          iterator_creator_train (object): NRMS data loader class for train data.
          iterator_creator_test (object): NRMS data loader class for test and validation data
      """
      self.word2vec_embedding = self._init_embedding(
          hparams.wordEmb_file
      )
  
      super().__init__(
          hparams,
          iterator_creator,
          seed=seed,
      )
  
file_path: recommenders/recommenders/models/newsrec/models/nrms.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 AttLayer2, SelfAttention
label_desc: Use image node_id 1 to create a new NRMSModel object from inherited base classes: BaseModel with example: obj = NRMSModel(hparams, iterator_creator, seed)