class_docstr: Test class for `SacreBLEUScore` metric.
class_docstr_tok: ["Test","class","for","`","SacreBLEUScore","`","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_bleu_score_differentiability(
      self, preds, targets, tokenize, lowercase
  ):
      """Test the differentiability of the metric, according to its `is_differentiable` attribute."""
      metric_args = {"tokenize": tokenize, "lowercase": lowercase}
  
      self.run_differentiability_test(
          preds=preds,
          targets=targets,
          metric_module=SacreBLEUScore,
          metric_functional=sacre_bleu_score,
          metric_args=metric_args,
      )
  
file_path: torchmetrics/tests/unittests/text/test_sacre_bleu.py
imports: from functools import partial
  from typing import Sequence
  import pytest
  from torch import Tensor, tensor
  from torchmetrics.functional.text.sacre_bleu import AVAILABLE_TOKENIZERS, _TokenizersLiteral, sacre_bleu_score
  from torchmetrics.text.sacre_bleu import SacreBLEUScore
  from torchmetrics.utilities.imports import _SACREBLEU_AVAILABLE
  from unittests.text.helpers import TextTester
  from unittests.text.inputs import _inputs_multiple_references
label_desc: Use image node_id 3 for calling the TestSacreBLEUScore obj's underlying member method code with example usage: obj.test_bleu_score_differentiability(preds, targets, tokenize, lowercase) without return types