class_docstr: Recommend most popular items of the current session.
  
  Parameters
  ----------
  name: string, default: 'SPop'
      The name of the recommender model.
  
  use_session_popularity: boolean, optional, default: True
      When False, no item frequency from history items in current session are being used.
  
  References
  ----------
  Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk:
  Session-based Recommendations with Recurrent Neural Networks, ICLR 2016
code: def __init__(self, name="SPop", use_session_popularity=True):
      super().__init__(name=name, trainable=False)
      self.use_session_popularity = use_session_popularity
      self.item_freq = Counter()
  
file_path: cornac/cornac/models/spop/recom_spop.py
imports: from collections import Counter
  import numpy
  from ..recommender import NextItemRecommender
label_desc: Use image node_id 1 to create a new SPop object from inherited base classes: NextItemRecommender with example: obj = SPop(name, use_session_popularity)