Unable to augment Chinese, given corresponding language model.

[beyondguo]

Using Context-word-enbedding augmenter:

English:

text = 'hi how are you'
context_aug = naw.ContextualWordEmbsAug(
    model_path='bert-base-uncased', action="substitute")
augmented_text = context_aug.augment(text)
print("Original:")
print(text)
print("Augmented Text:")
print(augmented_text)

output is ok:

Original:
hi how are you
Augmented Text:
hi how some you

But for Chinese:

text = '咋就不行了？'
context_aug = naw.ContextualWordEmbsAug(
    model_path='hfl/chinese-roberta-wwm-ext', action="substitute")
augmented_text = context_aug.augment(text)
print("Original:")
print(text)
print("Augmented Text:")
print(augmented_text)

output is exactly the same with my input:

Original:
咋就不行了？
Augmented Text:
咋 就 不 行 了 ？

I have checked to source code and don't know what's going wrong, could you please help me? Thanks a lot!!!

[beyondguo]

Update: I found that using bert-base-multilingual-uncased will be fine:

text = '咋就不行了？'
context_aug = naw.ContextualWordEmbsAug(
    model_path='bert-base-multilingual-uncased', action="substitute")
augmented_text = context_aug.augment(text)
print("Original:")
print(text)
print("Augmented Text:")
print(augmented_text)
>>>>>>>>
Original:
咋就不行了？
Augmented Text:
咋 就 通 行 了 ？

So what's the problem with hfl/chinese-roberta-wwm-ext?

[makcedward]

let use "bert-base-multilingual-uncased" as a workaround. will look into "hfl/chinese-roberta-wwm-ext" model.

[rajah]

Even though they are roberta models, they have to be loaded using bert type. model_type='bert' as a param will fix the issue.