class_docstr: Testing of Root Mean Square Error With Sliding Window.
class_docstr_tok: ["Testing","of","Root","Mean","Square","Error","With","Sliding","Window","."]
docstr: Test class implementation of metric.
docstr_tok: ["Test","class","implementation","of","metric","."]
code: def test_rmse_sw(self, preds, target, window_size, ddp):
      """Test class implementation of metric."""
      self.run_class_metric_test(
          ddp,
          preds,
          target,
          RootMeanSquaredErrorUsingSlidingWindow,
          partial(_sewar_rmse_sw, window_size=window_size),
          metric_args={"window_size": window_size},
      )
  
file_path: torchmetrics/tests/unittests/image/test_rmse_sw.py
imports: from functools import partial
  from typing import NamedTuple
  import pytest
  import sewar
  import torch
  from torch import Tensor
  from torchmetrics.functional import root_mean_squared_error_using_sliding_window
  from torchmetrics.image import RootMeanSquaredErrorUsingSlidingWindow
  from unittests import BATCH_SIZE, NUM_BATCHES
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 1 for calling the TestRootMeanSquareErrorWithSlidingWindow obj's underlying member method code with example usage: obj.test_rmse_sw(preds, target, window_size, ddp) without return types