code: def __init__(self, data_dir=cora_dir, data_type="all"):
      super(MovieLens_1M, self).__init__(data_dir, data_type)
      self.source_url = (
          "http://files.grouplens.org/datasets/movielens/ml-1m.zip"
      )
      self.origin_files = [
          "ml-1m/movies.dat",
          "ml-1m/ratings.dat",
          "ml-1m/users.dat",
      ]
      self.max_node_id = 9992
      self.train_node_type = ["train"]
      self.train_edge_type = ["train"]
      self.total_size = 9992
      self.all_node_type = -1
      self.all_edge_type = ["train", "train_removed"]
      self.id_file = os.path.join(data_dir, "ml_1m_test.id")
  
      self.genre = [
          "Action",
          "Adventure",
          "Animation",
          "Children's",
          "Comedy",
          "Crime",
          "Documentary",
          "Drama",
          "Fantasy",
          "Film-Noir",
          "Horror",
          "Musical",
          "Mystery",
          "Romance",
          "Sci-Fi",
          "Thriller",
          "War",
          "Western",
      ]
      self.genre_map = {
          key: i for key, i in zip(self.genre, range(len(self.genre)))
      }
      self.gender_map = {"M": 0, "F": 1}
      self.age_map = {
          "1": 0,
          "18": 1,
          "25": 2,
          "35": 3,
          "45": 4,
          "50": 5,
          "56": 6,
      }
      self.movie_len = 3952
  
file_path: euler/tf_euler/python/dataset/ml_1m.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import json
  import tqdm
  import urllib
  import zipfile
  import numpy
  from tf_euler.python.dataset.base_dataset import DataSet
label_desc: Use image node_id 1 to create a new MovieLens_1M object from inherited base classes: DataSet with example: obj = MovieLens_1M(data_dir, data_type)