code: def test_same_result_as_individual():
      """Test that the feature share wrapper gives the same result as the individual metrics."""
      fid = FrechetInceptionDistance(feature=768)
      inception = InceptionScore(feature=768)
      kid = KernelInceptionDistance(
          feature=768, subset_size=10, subsets=2
      )
  
      fs = FeatureShare([fid, inception, kid])
  
      x = torch.randint(255, (50, 3, 64, 64), dtype=torch.uint8)
      fs.update(x, real=True)
      fid.update(x, real=True)
      inception.update(x)
      kid.update(x, real=True)
      x = torch.randint(255, (50, 3, 64, 64), dtype=torch.uint8)
      fs.update(x, real=False)
      fid.update(x, real=False)
      inception.update(x)
      kid.update(x, real=False)
  
      fs_res = fs.compute()
      fid_res = fid.compute()
      inception_res = inception.compute()
      kid_res = kid.compute()
  
      assert fs_res["FrechetInceptionDistance"] == fid_res
      assert fs_res["InceptionScore"][0] == inception_res[0]
      assert fs_res["InceptionScore"][1] == inception_res[1]
      assert fs_res["KernelInceptionDistance"][0] == kid_res[0]
      assert fs_res["KernelInceptionDistance"][1] == kid_res[1]
  
file_path: torchmetrics/tests/unittests/wrappers/test_feature_share.py
imports: import pytest
  import torch
  from torchmetrics import MetricCollection
  from torchmetrics.image import FrechetInceptionDistance, InceptionScore, KernelInceptionDistance, LearnedPerceptualImagePatchSimilarity, StructuralSimilarityIndexMeasure
  from torchmetrics.wrappers import FeatureShare
label_desc: Use image node_id 6 for calling a global function with example usage: test_same_result_as_individual() without return types