code: def training_step(self, batch, batch_idx):
      assert torch.tensor([1.2, 3.4j]).dtype == torch.complex128
      return super().training_step(batch, batch_idx)
  
imports: import pickle
  from unittest.mock import MagicMock
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.plugins.precision.double import DoublePrecision
  from torch.utils.data import DataLoader, Dataset
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 4 for calling the DoublePrecisionBoringModelComplexBuffer obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: super