class_docstr: The Dataset class stores a sequence of data points for training or evaluation. 
  
  Parameters
  ----------
  raw_data: numpy structured array
      Input raw data.
  max_user: int
      Maximum number of users in the recommendation system.
  max_item: int
      Maximum number of items in the recommendation system.
  name: str
      Name of the dataset. 
  
  Notes  
  -----
  The Dataset class expects :code:`raw_data` as a numpy structured array, where each row represents a data 
  point and contains *at least* two keys:
  
  * :code:`user_id`: the user involved in the interaction.
  * :code:`item_id`: the item involved in the interaction.
  
  :code:`raw_data` might contain other keys, such as :code:`timestamp`, and :code:`location`, etc.
  based on the use cases of different recommendation systems. An user should be uniquely and numerically indexed 
  from 0 to :code:`total_number_of_users - 1`. The items should be indexed likewise.
docstr: Maximum number of users.
  
  Returns
  -------
  int
      Maximum number of users.
docstr_tok: ["Maximum","number","of","users",".","Returns","--","--","--","-","int","Maximum","number","of","users","."]
code: def max_user(self):
      """Maximum number of users.
  
      Returns
      -------
      int
          Maximum number of users.
      """
      return self._max_user
  
imports: import numpy
label_desc: Use image node_id 2 for calling the Dataset obj's underlying member method code with example usage: obj.max_user() and returns: self