refactor: ter (#713)

* translation_edit_rate
* TranslationEditRate
* docs

CHANGELOG.md

@@ -16,7 +16,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - `WordInfoLost` and `WordInfoPreserved` ([#630](https://github.com/PyTorchLightning/metrics/pull/630))
   - `SQuAD` ([#623](https://github.com/PyTorchLightning/metrics/pull/623))
   - `CHRFScore` ([#641](https://github.com/PyTorchLightning/metrics/pull/641))
-  - `TER` ([#646](https://github.com/PyTorchLightning/metrics/pull/646))
+  - `TranslationEditRate` ([#646](https://github.com/PyTorchLightning/metrics/pull/646))
 
 
 - Added a default VSCode devcontainer configuration ([#621](https://github.com/PyTorchLightning/metrics/pull/621))

docs/source/references/functional.rst

@@ -477,10 +477,10 @@ squad [func]
 .. autofunction:: torchmetrics.functional.squad
     :noindex:
 
-ter [func]
-~~~~~~~~~~
+translation_edit_rate [func]
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: torchmetrics.functional.ter
+.. autofunction:: torchmetrics.functional.translation_edit_rate
     :noindex:
 
 wer [func]

docs/source/references/modules.rst

@@ -658,10 +658,10 @@ SQuAD
 .. autoclass:: torchmetrics.SQuAD
     :noindex:
 
-TER
-~~~
+TranslationEditRate
+~~~~~~~~~~~~~~~~~~~
 
-.. autoclass:: torchmetrics.TER
+.. autoclass:: torchmetrics.TranslationEditRate
     :noindex:
 
 WER

tests/text/test_ter.py

@@ -6,8 +6,8 @@
 
 from tests.text.helpers import TextTester
 from tests.text.inputs import _inputs_multiple_references, _inputs_single_sentence_multiple_references
-from torchmetrics.functional.text.ter import ter
-from torchmetrics.text.ter import TER
+from torchmetrics.functional.text.ter import translation_edit_rate
+from torchmetrics.text.ter import TranslationEditRate
 from torchmetrics.utilities.imports import _SACREBLEU_AVAILABLE
 
 if _SACREBLEU_AVAILABLE:
@@ -71,7 +71,7 @@ def test_chrf_score_class(
             ddp=ddp,
             preds=preds,
             targets=targets,
-            metric_class=TER,
+            metric_class=TranslationEditRate,
             sk_metric=nltk_metric,
             dist_sync_on_step=dist_sync_on_step,
             metric_args=metric_args,
@@ -95,7 +95,7 @@ def test_ter_score_functional(self, preds, targets, normalize, no_punctuation, a
         self.run_functional_metric_test(
             preds,
             targets,
-            metric_functional=ter,
+            metric_functional=translation_edit_rate,
             sk_metric=nltk_metric,
             metric_args=metric_args,
         )
@@ -111,20 +111,20 @@ def test_chrf_score_differentiability(self, preds, targets, normalize, no_punctu
         self.run_differentiability_test(
             preds=preds,
             targets=targets,
-            metric_module=TER,
-            metric_functional=ter,
+            metric_module=TranslationEditRate,
+            metric_functional=translation_edit_rate,
             metric_args=metric_args,
         )
 
 
 def test_ter_empty_functional():
     hyp = []
     ref = [[]]
-    assert ter(hyp, ref) == tensor(0.0)
+    assert translation_edit_rate(hyp, ref) == tensor(0.0)
 
 
 def test_ter_empty_class():
-    ter_metric = TER()
+    ter_metric = TranslationEditRate()
     hyp = []
     ref = [[]]
     assert ter_metric(hyp, ref) == tensor(0.0)
@@ -133,11 +133,11 @@ def test_ter_empty_class():
 def test_ter_empty_with_non_empty_hyp_functional():
     hyp = ["python"]
     ref = [[]]
-    assert ter(hyp, ref) == tensor(0.0)
+    assert translation_edit_rate(hyp, ref) == tensor(0.0)
 
 
 def test_ter_empty_with_non_empty_hyp_class():
-    ter_metric = TER()
+    ter_metric = TranslationEditRate()
     hyp = ["python"]
     ref = [[]]
     assert ter_metric(hyp, ref) == tensor(0.0)
@@ -146,12 +146,12 @@ def test_ter_empty_with_non_empty_hyp_class():
 def test_ter_return_sentence_level_score_functional():
     hyp = _inputs_single_sentence_multiple_references.preds
     ref = _inputs_single_sentence_multiple_references.targets
-    _, sentence_ter = ter(hyp, ref, return_sentence_level_score=True)
+    _, sentence_ter = translation_edit_rate(hyp, ref, return_sentence_level_score=True)
     isinstance(sentence_ter, Tensor)
 
 
 def test_ter_return_sentence_level_class():
-    ter_metric = TER(return_sentence_level_score=True)
+    ter_metric = TranslationEditRate(return_sentence_level_score=True)
     hyp = _inputs_single_sentence_multiple_references.preds
     ref = _inputs_single_sentence_multiple_references.targets
     _, sentence_ter = ter_metric(hyp, ref)

torchmetrics/__init__.py

@@ -70,14 +70,14 @@
     RetrievalRPrecision,
 )
 from torchmetrics.text import (  # noqa: E402
-    TER,
     WER,
     BLEUScore,
     CharErrorRate,
     CHRFScore,
     MatchErrorRate,
     SacreBLEUScore,
     SQuAD,
+    TranslationEditRate,
     WordInfoLost,
     WordInfoPreserved,
 )
@@ -152,7 +152,7 @@
     "StatScores",
     "SumMetric",
     "SymmetricMeanAbsolutePercentageError",
-    "TER",
+    "TranslationEditRate",
     "WER",
     "CharErrorRate",
     "MatchErrorRate",

torchmetrics/functional/__init__.py

@@ -72,7 +72,7 @@
 from torchmetrics.functional.text.rouge import rouge_score
 from torchmetrics.functional.text.sacre_bleu import sacre_bleu_score
 from torchmetrics.functional.text.squad import squad
-from torchmetrics.functional.text.ter import ter
+from torchmetrics.functional.text.ter import translation_edit_rate
 from torchmetrics.functional.text.wer import wer
 from torchmetrics.functional.text.wil import word_information_lost
 from torchmetrics.functional.text.wip import word_information_preserved
@@ -138,7 +138,7 @@
     "ssim",
     "stat_scores",
     "symmetric_mean_absolute_percentage_error",
-    "ter",
+    "translation_edit_rate",
     "wer",
     "char_error_rate",
     "match_error_rate",

torchmetrics/functional/text/__init__.py

@@ -18,7 +18,7 @@
 from torchmetrics.functional.text.mer import match_error_rate  # noqa: F401
 from torchmetrics.functional.text.sacre_bleu import sacre_bleu_score  # noqa: F401
 from torchmetrics.functional.text.squad import squad  # noqa: F401
-from torchmetrics.functional.text.ter import ter  # noqa: F401
+from torchmetrics.functional.text.ter import translation_edit_rate  # noqa: F401
 from torchmetrics.functional.text.wer import wer  # noqa: F401
 from torchmetrics.functional.text.wil import word_information_lost  # noqa: F401
 from torchmetrics.functional.text.wip import word_information_preserved  # noqa: F401

torchmetrics/functional/text/ter.py

@@ -557,7 +557,7 @@ def _ter_compute(total_num_edits: Tensor, total_ref_length: Tensor) -> Tensor:
     return _compute_ter_score_from_statistics(total_num_edits, total_ref_length)
 
 
-def ter(
+def translation_edit_rate(
     hypothesis_corpus: Union[str, Sequence[str]],
     reference_corpus: Sequence[Union[str, Sequence[str]]],
     normalize: bool = False,
@@ -594,7 +594,7 @@ def ter(
     Example:
         >>> hypothesis_corpus = ['the cat is on the mat']
         >>> reference_corpus = [['there is a cat on the mat', 'a cat is on the mat']]
-        >>> ter(hypothesis_corpus, reference_corpus)
+        >>> translation_edit_rate(hypothesis_corpus, reference_corpus)
         tensor(0.1538)
 
     References:

torchmetrics/text/__init__.py

@@ -17,7 +17,7 @@
 from torchmetrics.text.mer import MatchErrorRate  # noqa: F401
 from torchmetrics.text.sacre_bleu import SacreBLEUScore  # noqa: F401
 from torchmetrics.text.squad import SQuAD  # noqa: F401
-from torchmetrics.text.ter import TER  # noqa: F401
+from torchmetrics.text.ter import TranslationEditRate  # noqa: F401
 from torchmetrics.text.wer import WER  # noqa: F401
 from torchmetrics.text.wil import WordInfoLost  # noqa: F401
 from torchmetrics.text.wip import WordInfoPreserved  # noqa: F401

torchmetrics/text/ter.py

@@ -21,7 +21,7 @@
 from torchmetrics.metric import Metric
 
 
-class TER(Metric):
+class TranslationEditRate(Metric):
     """Calculate Translation edit rate (`TER`_)  of machine translated text with one or more references. This
     implementation follows the implmenetaions from
     https://github.com/mjpost/sacrebleu/blob/master/sacrebleu/metrics/ter.py. The `sacrebleu` implmenetation is a
@@ -52,7 +52,7 @@ class TER(Metric):
     Example:
         >>> hypothesis_corpus = ['the cat is on the mat']
         >>> reference_corpus = [['there is a cat on the mat', 'a cat is on the mat']]
-        >>> metric = TER()
+        >>> metric = TranslationEditRate()
         >>> metric(hypothesis_corpus, reference_corpus)
         tensor(0.1538)