docstr: - h,r->t: Given head and relation, predict target entities
      - hr: np.ndarray of shape (num_test_triplets, 2)
            i-th row stores i-th (h,r)
docstr_tok: ["-","h",",","r-",">","t",":","Given","head","and","relation",",","predict","target","entities","-","hr",":","np.ndarray","of","shape","(","num_test_triplets",",","2",")","i-th","row","stores","i-th","(","h",",","r",")"]
code: def test_dict(self, mode: str) -> Dict[str, Dict[str, np.ndarray]]:
      """
      - h,r->t: Given head and relation, predict target entities
          - hr: np.ndarray of shape (num_test_triplets, 2)
                i-th row stores i-th (h,r)
      """
      assert mode in ["test-dev", "test-challenge"]
  
      if mode == "test-dev":
          if self._test_dev_dict is None:
              self._test_dev_dict = {}
              # h, r -> t
              self._test_dev_dict["h,r->t"] = {}
              self._test_dev_dict["h,r->t"]["hr"] = np.load(
                  osp.join(self.processed_dir, "test-dev_hr.npy")
              )
          return self._test_dev_dict
  
      elif mode == "test-challenge":
          if self._test_challenge_dict is None:
              self._test_challenge_dict = {}
              # h, r -> t
              self._test_challenge_dict["h,r->t"] = {}
              self._test_challenge_dict["h,r->t"]["hr"] = np.load(
                  osp.join(self.processed_dir, "test-challenge_hr.npy")
              )
          return self._test_challenge_dict
  
imports: from typing import Optional, Union, Dict
  import os
  import shutil
  import os.path
  import torch
  import numpy
  import pandas
  from ogb.utils.url import decide_download, download_url, extract_zip, makedirs
label_desc: Use image node_id 12 for calling the WikiKG90Mv2Dataset obj's underlying member method code with example usage: obj.test_dict(mode) and returns: self, self