class_docstr: The :obj:`ogbn-mag` dataset from the `"Open Graph Benchmark: Datasets
  for Machine Learning on Graphs" <https://arxiv.org/abs/2005.00687>`_ paper.
  :obj:`ogbn-mag` is a heterogeneous graph composed of a subset of the
  Microsoft Academic Graph (MAG).
  It contains four types of entities — papers (736,389 nodes), authors
  (1,134,649 nodes), institutions (8,740 nodes), and fields of study
  (59,965 nodes) — as well as four types of directed relations connecting two
  types of entities.
  Each paper is associated with a 128-dimensional :obj:`word2vec` feature
  vector, while all other node types are not associated with any input
  features.
  The task is to predict the venue (conference or journal) of each paper.
  In total, there are 349 different venues.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      preprocess (str, optional): Pre-processes the original dataset by
          adding structural features (:obj:`"metapath2vec"`, :obj:`"TransE"`)
          to featureless nodes. (default: :obj:`None`)
      transform (callable, optional): A function/transform that takes in an
          :obj:`torch_geometric.data.HeteroData` object and returns a
          transformed version. The data object will be transformed before
          every access. (default: :obj:`None`)
      pre_transform (callable, optional): A function/transform that takes in
          an :obj:`torch_geometric.data.HeteroData` object and returns a
          transformed version. The data object will be transformed before
          being saved to disk. (default: :obj:`None`)
      force_reload (bool, optional): Whether to re-process the dataset.
          (default: :obj:`False`)
class_docstr_tok: ["The",":","obj",":","`","ogbn-mag","`","dataset","from","the","`","``","Open","Graph","Benchmark",":","Datasets","for","Machine","Learning","on","Graphs","''","<","https",":","\/\/arxiv.org\/abs\/2005.00687",">","`","_","paper",".",":","obj",":","`","ogbn-mag","`","is","a","heterogeneous","graph","composed","of","a","subset","of","the","Microsoft","Academic","Graph","(","MAG",")",".","It","contains","four","types","of","entities","\u2014","papers","(","736,389","nodes",")",",","authors","(","1,134,649","nodes",")",",","institutions","(","8,740","nodes",")",",","and","fields","of","study","(","59,965","nodes",")","\u2014","as","well","as","four","types","of","directed","relations","connecting","two","types","of","entities",".","Each","paper","is","associated","with","a","128-dimensional",":","obj",":","`","word2vec","`","feature","vector",",","while","all","other","node","types","are","not","associated","with","any","input","features",".","The","task","is","to","predict","the","venue","(","conference","or","journal",")","of","each","paper",".","In","total",",","there","are","349","different","venues",".","Args",":","root","(","str",")",":","Root","directory","where","the","dataset","should","be","saved",".","preprocess","(","str",",","optional",")",":","Pre-processes","the","original","dataset","by","adding","structural","features","(",":","obj",":","`","``","metapath2vec","''","`",",",":","obj",":","`","``","TransE","''","`",")","to","featureless","nodes",".","(","default",":",":","obj",":","`","None","`",")","transform","(","callable",",","optional",")",":","A","function\/transform","that","takes","in","an",":","obj",":","`","torch_geometric.data.HeteroData","`","object","and","returns","a","transformed","version",".","The","data","object","will","be","transformed","before","every","access",".","(","default",":",":","obj",":","`","None","`",")","pre_transform","(","callable",",","optional",")",":","A","function\/transform","that","takes","in","an",":","obj",":","`","torch_geometric.data.HeteroData","`","object","and","returns","a","transformed","version",".","The","data","object","will","be","transformed","before","being","saved","to","disk",".","(","default",":",":","obj",":","`","None","`",")","force_reload","(","bool",",","optional",")",":","Whether","to","re-process","the","dataset",".","(","default",":",":","obj",":","`","False","`",")"]
code: def processed_dir(self) -> str:
      return osp.join(self.root, "mag", "processed")
  
file_path: pytorch_geometric/torch_geometric/datasets/ogb_mag.py
imports: import os
  import os.path
  import shutil
  from typing import Callable, List, Optional
  import numpy
  import torch
  from torch_geometric.data import HeteroData, InMemoryDataset, download_url, extract_zip
  from torch_geometric.io import fs
label_desc: Use image node_id 4 for calling the OGB_MAG obj's underlying member method code with example usage: obj.processed_dir() and returns: osp