code: def test_dtype_transfer_to_submodule():
      """Test that change in dtype also changes the default inception net."""
      imgs = torch.randn(1, 3, 256, 256)
      imgs = ((imgs.clamp(-1, 1) / 2 + 0.5) * 255).to(torch.uint8)
  
      metric = FrechetInceptionDistance(feature=64)
      metric.set_dtype(torch.float64)
  
      out = metric.inception(imgs)
      assert out.dtype == torch.float64
  
imports: import pickle
  from contextlib import nullcontext
  from functools import partial
  import pytest
  import torch
  from torch.nn import Module
  from torch.utils.data import Dataset
  from torchmetrics.image.fid import FrechetInceptionDistance, NoTrainInceptionV3
  from torchmetrics.utilities.imports import _TORCH_FIDELITY_AVAILABLE
label_desc: Use image node_id 10 for calling a global function with example usage: test_dtype_transfer_to_submodule() without return types