class_docstr: Test class for `ExplainedVariance` metric.
class_docstr_tok: ["Test","class","for","`","ExplainedVariance","`","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_explained_variance_differentiability(
      self, multioutput, preds, target, ref_metric
  ):
      """Test the differentiability of the metric, according to its `is_differentiable` attribute."""
      self.run_differentiability_test(
          preds=preds,
          target=target,
          metric_module=ExplainedVariance,
          metric_functional=explained_variance,
          metric_args={"multioutput": multioutput},
      )
  
file_path: torchmetrics/tests/unittests/regression/test_explained_variance.py
imports: from functools import partial
  import pytest
  import torch
  from sklearn.metrics import explained_variance_score
  from torchmetrics.functional import explained_variance
  from torchmetrics.regression import ExplainedVariance
  from unittests import BATCH_SIZE, 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 TestExplainedVariance obj's underlying member method code with example usage: obj.test_explained_variance_differentiability(multioutput, preds, target, ref_metric) without return types