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jiwer.wer(outputs_true, outputs_pred, standardize=True) #85

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hechengzhi985 opened this issue Jan 29, 2024 · 1 comment
Open

jiwer.wer(outputs_true, outputs_pred, standardize=True) #85

hechengzhi985 opened this issue Jan 29, 2024 · 1 comment

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@hechengzhi985
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Traceback (most recent call last):
File "main.py", line 222, in
main(0, args)
File "main.py", line 121, in main
model.fit(dataset_train,
File "EfficientConformer-master/models/model.py", line 344, in fit
raise e
File "EfficientConformer-master/models/model.py", line 303, in fit
wer, truths, preds, val_loss = self.evaluate(dataset, val_steps, verbose_val, eval_loss=True)
File "EfficientConformer-master/models/model.py", line 425, in evaluate
batch_wer = jiwer.wer(outputs_true, outputs_pred, standardize=True)
TypeError: wer() got an unexpected keyword argument 'standardize'

@nikvaessen
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nikvaessen commented Jan 29, 2024

The keyword standardize was removed since version 2.5.0. Eithet set jiwer<=2.4, or change the call:

import jiwer

jiwer.wer(
  outputs_true, 
  outputs_pred,
  reference_transform=jiwer.wer_standardize, 
  hypothesis_transform=jiwer.wer_standardize
)

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