From 31e9673eef3088f08e3ee6aef8b78abd701ca329 Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Sun, 4 Apr 2021 16:05:13 +0200
Subject: Reformat test for CER

---
 text_recognizer/models/metrics.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 text_recognizer/models/metrics.py

(limited to 'text_recognizer/models/metrics.py')

diff --git a/text_recognizer/models/metrics.py b/text_recognizer/models/metrics.py
new file mode 100644
index 0000000..58d0537
--- /dev/null
+++ b/text_recognizer/models/metrics.py
@@ -0,0 +1,32 @@
+"""Character Error Rate (CER)."""
+from typing import Sequence
+
+import editdistance
+import torch
+from torch import Tensor
+import torchmetrics
+
+
+class CharacterErrorRate(torchmetrics.Metric):
+    """Character error rate metric, computed using Levenshtein distance."""
+
+    def __init__(self, ignore_tokens: Sequence[int], *args) -> None:
+        super().__init__()
+        self.ignore_tokens = set(ignore_tokens)
+        self.add_state("error", default=torch.tensor(0.0), dist_reduce_fx="sum")
+        self.add_state("total", default=torch.tensor(0), dist_reduce_fx="sum")
+
+    def update(self, preds: Tensor, targets: Tensor) -> None:
+        """Update CER."""
+        bsz = preds.shape[0]
+        for index in range(bsz):
+            pred = [p for p in preds[index].tolist() if p not in self.ignore_tokens]
+            target = [t for t in targets[index].tolist() if t not in self.ignore_tokens]
+            distance = editdistance.distance(pred, target)
+            error = distance / max(len(pred), len(target))
+            self.error += error
+        self.total += bsz
+
+    def compute(self) -> Tensor:
+        """Compute CER."""
+        return self.error / self.total
-- 
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