code: def test_step(self, batch, batch_idx):
      assert batch.dtype == torch.float64
      output = self.layer(batch)
      assert output.dtype == torch.float64
      loss = self.loss(output)
      return {"y": loss}
  
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 3 for calling the DoublePrecisionBoringModelNoForward obj's underlying member method code with example usage: obj.test_step(batch, batch_idx) and returns: dict