code: def test_step(self, batch, batch_idx):
      assert batch.dtype == torch.float64
      assert torch.tensor([0.0]).dtype == torch.float64
      assert (
          torch.tensor([0.0], dtype=torch.float16).dtype
          == torch.float16
      )
      return super().test_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 DoublePrecisionBoringModel obj's underlying member method code with example usage: obj.test_step(batch, batch_idx) and returns: super