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 fit(self, train_set, val_set=None):
      super().fit(train_set=train_set, val_set=val_set)
      self.item_freq = Counter(self.train_set.uir_tuple[1])
      return self
  
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 2 for calling the SPop obj's underlying member method code with example usage: obj.fit(train_set, val_set) and returns: self