docstr: Construct a dictionary that maps graph elements to values.
  
  Args:
      data_dict (dict): A dictionary that maps string name to numpy arrays.
  
  Returns:
      dict: A dictionary that maps graph elements to numpy arrays.
docstr_tok: ["Construct","a","dictionary","that","maps","graph","elements","to","values",".","Args",":","data_dict","(","dict",")",":","A","dictionary","that","maps","string","name","to","numpy","arrays",".","Returns",":","dict",":","A","dictionary","that","maps","graph","elements","to","numpy","arrays","."]
code: def gen_feed_dict(self, data_dict):
      """Construct a dictionary that maps graph elements to values.
  
      Args:
          data_dict (dict): A dictionary that maps string name to numpy arrays.
  
      Returns:
          dict: A dictionary that maps graph elements to numpy arrays.
  
      """
      if not data_dict:
          return dict()
      feed_dict = {
          self.labels: data_dict["labels"],
          self.users: data_dict["users"],
          self.items: data_dict["items"],
          self.cates: data_dict["cates"],
          self.item_history: data_dict["item_history"],
          self.item_cate_history: data_dict["item_cate_history"],
          self.mask: data_dict["mask"],
          self.time: data_dict["time"],
          self.time_diff: data_dict["time_diff"],
          self.time_from_first_action: data_dict[
              "time_from_first_action"
          ],
          self.time_to_now: data_dict["time_to_now"],
      }
      return feed_dict
  
file_path: recommenders/recommenders/models/deeprec/io/sequential_iterator.py
imports: import tensorflow
  import numpy
  import random
  from recommenders.models.deeprec.io.iterator import BaseIterator
  from recommenders.models.deeprec.deeprec_utils import load_dict
label_desc: Use image node_id 6 for calling the SequentialIterator obj's underlying member method code with example usage: obj.gen_feed_dict(data_dict) and returns: feed_dict, dict