typo

Co-authored-by: Justus Schock <[email protected]>

torchmetrics/__init__.py

@@ -69,13 +69,13 @@
 from torchmetrics.text import (  # noqa: E402
     TER,
     WER,
-    WordErrorRate,
     BLEUScore,
     CharErrorRate,
     CHRFScore,
     MatchErrorRate,
     SacreBLEUScore,
     SQuAD,
+    WordErrorRate,
     WordInfoLost,
     WordInfoPreserved,
 )

torchmetrics/functional/__init__.py

@@ -73,7 +73,7 @@
 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.wer import web, word_error_rate
+from torchmetrics.functional.text.wer import wer, word_error_rate
 from torchmetrics.functional.text.wil import word_information_lost
 from torchmetrics.functional.text.wip import word_information_preserved
 
@@ -139,7 +139,7 @@
     "stat_scores",
     "symmetric_mean_absolute_percentage_error",
     "ter",
-    "web",
+    "wer",
     "word_error_rate",
     "char_error_rate",
     "match_error_rate",

torchmetrics/functional/text/__init__.py

@@ -19,6 +19,6 @@
 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.wer import web, word_error_rate  # noqa: F401
+from torchmetrics.functional.text.wer import wer, word_error_rate  # 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/wer.py

@@ -87,7 +87,7 @@ def word_error_rate(
     return _wer_compute(errors, total)
 
 
-def web(
+def wer(
     predictions: Union[str, List[str]],
     references: Union[str, List[str]],
 ) -> Tensor:
@@ -99,8 +99,8 @@ def web(
     Examples:
         >>> predictions = ["this is the prediction", "there is an other sample"]
         >>> references = ["this is the reference", "there is another one"]
-        >>> web(predictions=predictions, references=references)
+        >>> wer(predictions=predictions, references=references)
         tensor(0.5000)
     """
-    warn("`web` was renamed to `word_error_rate` in v0.7 and it will be removed in v0.8", DeprecationWarning)
+    warn("`wer` was renamed to `word_error_rate` in v0.7 and it will be removed in v0.8", DeprecationWarning)
     return word_error_rate(predictions, references)

torchmetrics/text/__init__.py

@@ -18,6 +18,6 @@
 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.wer import WordErrorRate, WER  # noqa: F401
+from torchmetrics.text.wer import WER, WordErrorRate  # noqa: F401
 from torchmetrics.text.wil import WordInfoLost  # noqa: F401
 from torchmetrics.text.wip import WordInfoPreserved  # noqa: F401

torchmetrics/text/wer.py

@@ -125,10 +125,5 @@ def __init__(
         process_group: Optional[Any] = None,
         dist_sync_fn: Callable = None,
     ):
-        warn("`WEB` was renamed to `WordErrorRate` in v0.7 and it will be removed in v0.8", DeprecationWarning)
-        super().__init__(
-            compute_on_step,
-                                    dist_sync_on_step,
-                                                              process_group,
-                                                                                             dist_sync_fn
-        )
+        warn("`WER` was renamed to `WordErrorRate` in v0.7 and it will be removed in v0.8", DeprecationWarning)
+        super().__init__(compute_on_step, dist_sync_on_step, process_group, dist_sync_fn)