class_docstr: Test class for `FleissKappa` metric.
class_docstr_tok: ["Test","class","for","`","FleissKappa","`","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_fleiss_kappa_differentiability(self, preds, target, mode):
      """Test the differentiability of the metric, according to its `is_differentiable` attribute."""
      self.run_differentiability_test(
          preds,
          target,
          metric_module=WrappedFleissKappa,
          metric_functional=wrapped_fleiss_kappa,
          metric_args={"mode": mode},
      )
  
file_path: torchmetrics/tests/unittests/nominal/test_fleiss_kappa.py
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from statsmodels.stats.inter_rater import fleiss_kappa
  from torchmetrics.functional.nominal.fleiss_kappa import fleiss_kappa
  from torchmetrics.nominal.fleiss_kappa import FleissKappa
  from unittests import BATCH_SIZE, NUM_BATCHES, NUM_CLASSES
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 3 for calling the TestFleissKappa obj's underlying member method code with example usage: obj.test_fleiss_kappa_differentiability(preds, target, mode) without return types