class_docstr: Test class for `WordInfoLost` 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_wil_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=WordInfoLost,
          metric_functional=word_information_lost,
      )
  
file_path: torchmetrics/tests/unittests/text/test_wil.py
imports: from typing import List, Union
  import pytest
  from jiwer import wil
  from torchmetrics.functional.text.wil import word_information_lost
  from torchmetrics.text.wil import WordInfoLost
  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 TestWordInfoLost obj's underlying member method code with example usage: obj.test_wil_differentiability(preds, targets) without return types