graphlearn_torch/python/data/table_dataset.py [112:125]:
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                                           num_threads=reader_threads,
                                           capacity=reader_capacity)
      while True:
        try:
          data = reader.read(reader_batch_size, allow_smaller_final_batch=True)
          feature_list.extend(data)
          step += 1
        except common_io.exception.OutOfRangeException:
          reader.close()
          break
        if step % 1000 == 0:
          print(f"{datetime.datetime.now()}: load "
                f"{step * reader_batch_size} nodes.")
      ids = torch.tensor([feat[0] for feat in feature_list], dtype=torch.long)
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graphlearn_torch/python/distributed/dist_table_dataset.py [259:272]:
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                                           num_threads=reader_threads,
                                           capacity=reader_capacity)
      while True:
        try:
          data = reader.read(reader_batch_size, allow_smaller_final_batch=True)
          feature_list.extend(data)
          step += 1
        except common_io.exception.OutOfRangeException:
          reader.close()
          break
        if step % 1000 == 0:
          print(f"{datetime.datetime.now()}: load "
                f"{step * reader_batch_size} nodes.")
      ids = torch.tensor([feat[0] for feat in feature_list], dtype=torch.long)
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