model.save：TypeError: Object of type module is not JSON serializable

[asd8095075]

from kashgari.corpus import ChineseDailyNerCorpus
from kashgari.embeddings import BertEmbedding
from kashgari.tasks.labeling import BiLSTM_CRF_Modelb
import kashgari

X_train, y_train = ChineseDailyNerCorpus.load_data('train')
x_test, y_test = ChineseDailyNerCorpus.load_data('test')
X_valid, y_valid = ChineseDailyNerCorpus.load_data('valid')

bert_embed = BertEmbedding('./bert/chinese_roberta_wwm_ext_L-12_H-768_A-12',
task=kashgari.tasks.labeling,
sequence_length=100)

model = BiLSTM_CRF_Model(bert_embed)
model.fit(X_train, y_train, X_valid, y_valid, epochs=1,batch_size=512)

[asd8095075]

Version being used： kashgari2.0.0
Operating system： windows 10
Version of Python： 3.7.2
Errors in console： TypeError: Object of type module is not JSON serializable
Detailed description of the problem： use chinese_roberta_wwm_ext_L-12_H-768_A-12，save model fail

[Cliccker]

I've met the same problem while training a labeling model.
Did you find any solution?

[asd8095075]

The problem remains unsolved

[cccccrj]

also encountered this problem.

[HuizhiXu]

got this problem too

[HuizhiXu]

I tried to find why this happened.

I have located the problem, it’s in this file “lib/python3.6/site-packages/kashgari/tasks/abs_task_model.py”
in function save , line 84, f.write(json.dumps(self.to_dict(), indent=2, ensure_ascii=False)).

The structure of “module” might have wrong type, not JSON, so it cannot be serializied.

Also noticed that Keras has the same issue. keras-team/keras#9342
I’ve changed the source file of Keras, but nothing has changed.

my Setup：
tf 2.2.0
Ubuntu 20.04
kashgari 2.0.2
keras 2.3.1
cuda toolkit 10.1
cuDNN 7.6

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

[cjrcjr]

我把
bert_embed = BertEmbedding('./bert/chinese_roberta_wwm_ext_L-12_H-768_A-12',
task=kashgari.tasks.labeling,
sequence_length=100)
改为
bert_embed = BertEmbedding('./bert/chinese_roberta_wwm_ext_L-12_H-768_A-12')
就能成功保存模型了，反正不传入task就可以保存