class_docstr: Dataset for test data in WikiKG90M
  
  Args:
      triplets (dict):
          The collection of test data with keys 'h', 'r',
          'candidate_t', 't_correct_index'.
          The values of 'h', 'r' and 't_correct_index' are 1D np.ndarray.
          The values of 'candidate_t' are 2D np.ndarray.
class_docstr_tok: ["Dataset","for","test","data","in","WikiKG90M","Args",":","triplets","(","dict",")",":","The","collection","of","test","data","with","keys","'","h","'",",","'","r","'",",","'candidate_t","'",",","'t_correct_index","'",".","The","values","of","'","h","'",",","'","r","'","and","'t_correct_index","'","are","1D","np.ndarray",".","The","values","of","'candidate_t","'","are","2D","np.ndarray","."]
code: def __init__(self, triplets):
      self._h = triplets["h"]
      self._r = triplets["r"]
      self._candidate = triplets["candidate_t"]
      self._t_index = triplets.get("t_correct_index", None)
  
imports: import os
  import numpy
  from numpy.random import default_rng
  import paddle
  from paddle.io import Dataset
  from paddle.io import DataLoader, DistributedBatchSampler
  from utils import timer_wrapper
label_desc: Use image node_id 1 to create a new TestWikiKG90M object from inherited base classes: Dataset with example: obj = TestWikiKG90M(triplets)