class_docstr: Test class for `MultiScaleStructuralSimilarityIndexMeasure` metric.
docstr: Test the differentiability of the metric, according to its `is_differentiable` attribute.
docstr_tok: ["Test","the","differentiability","of","the","metric",",","according","to","its","`","is_differentiable","`","attribute","."]
code: def test_ms_ssim_differentiability(self, preds, target):
      """Test the differentiability of the metric, according to its `is_differentiable` attribute."""
      # We need to minimize this example to make the test tractable
      single_beta = (1.0,)
      _preds = preds[:, :, :, :16, :16]
      _target = target[:, :, :, :16, :16]
  
      self.run_differentiability_test(
          _preds.type(torch.float64),
          _target.type(torch.float64),
          metric_functional=multiscale_structural_similarity_index_measure,
          metric_module=MultiScaleStructuralSimilarityIndexMeasure,
          metric_args={
              "data_range": 1.0,
              "kernel_size": 11,
              "betas": single_beta,
          },
      )
  
file_path: torchmetrics/tests/unittests/image/test_ms_ssim.py
imports: from functools import partial
  import pytest
  import torch
  from pytorch_msssim import ms_ssim
  from torchmetrics.functional.image.ssim import multiscale_structural_similarity_index_measure
  from torchmetrics.image.ssim import MultiScaleStructuralSimilarityIndexMeasure
  from unittests import NUM_BATCHES, _Input
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 3 for calling the TestMultiScaleStructuralSimilarityIndexMeasure obj's underlying member method code with example usage: obj.test_ms_ssim_differentiability(preds, target) without return types