code: def test_kid_same_input(feature):
      """Test that the metric works."""
      metric = KernelInceptionDistance(
          feature=feature, subsets=5, subset_size=2
      )
  
      for _ in range(2):
          img = torch.randint(
              0, 255, (10, 3, 299, 299), dtype=torch.uint8
          )
          metric.update(img, real=True)
          metric.update(img, real=False)
  
      assert torch.allclose(
          torch.cat(metric.real_features, dim=0),
          torch.cat(metric.fake_features, dim=0),
      )
  
      mean, std = metric.compute()
      assert mean != 0.0
      assert std >= 0.0
  
imports: import pickle
  from contextlib import nullcontext
  import pytest
  import torch
  from torch.nn import Module
  from torch.utils.data import Dataset
  from torchmetrics.image.kid import KernelInceptionDistance
  from torchmetrics.utilities.imports import _TORCH_FIDELITY_AVAILABLE
label_desc: Use image node_id 5 for calling a global function with example usage: test_kid_same_input(feature) without return types