class_docstr: Test class for `WordErrorRate` metric.
class_docstr_tok: ["Test","class","for","`","WordErrorRate","`","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_wer_differentiability(self, preds, targets):
      """Test the differentiability of the metric, according to its `is_differentiable` attribute."""
      self.run_differentiability_test(
          preds=preds,
          targets=targets,
          metric_module=WordErrorRate,
          metric_functional=word_error_rate,
      )
  
file_path: torchmetrics/tests/unittests/text/test_wer.py
imports: from typing import Callable, List, Union
  import pytest
  from torchmetrics.functional.text.wer import word_error_rate
  from torchmetrics.text.wer import WordErrorRate
  from torchmetrics.utilities.imports import _JIWER_AVAILABLE
  from unittests.text.helpers import TextTester
  from unittests.text.inputs import _inputs_error_rate_batch_size_1, _inputs_error_rate_batch_size_2
label_desc: Use image node_id 3 for calling the TestWER obj's underlying member method code with example usage: obj.test_wer_differentiability(preds, targets) without return types