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"""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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