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🐛 Fixing multi label classification model loading. #304 #305

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Merged
BrikerMan merged 1 commit into from
Dec 7, 2019
Merged

🐛 Fixing multi label classification model loading. #304 #305

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6 changes: 5 additions & 1 deletion kashgari/processors/classification_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,11 @@ class ClassificationProcessor(BaseProcessor):
def __init__(self, multi_label=False, **kwargs):
super(ClassificationProcessor, self).__init__(**kwargs)
self.multi_label = multi_label
self.multi_label_binarizer: MultiLabelBinarizer = None
if self.label2idx:
self.multi_label_binarizer: MultiLabelBinarizer = MultiLabelBinarizer(classes=list(self.label2idx.keys()))
self.multi_label_binarizer.fit([])
else:
self.multi_label_binarizer: MultiLabelBinarizer = None

def info(self):
info = super(ClassificationProcessor, self).info()
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6 changes: 6 additions & 0 deletions tests/classification/test_bi_lstm.py
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Expand Up @@ -133,6 +133,12 @@ def test_multi_label(self):
assert isinstance(model.predict(sample_eval_x)[0], tuple)
report_dict = model.evaluate(sample_eval_x, sample_eval_y, output_dict=True)
assert isinstance(report_dict, dict)
res = model.predict(valid_x[:20])
model_path = os.path.join(tempfile.gettempdir(), str(time.time()))
model.save(model_path)

new_model = kashgari.utils.load_model(model_path)
assert res == new_model.predict(valid_x[:20])


if __name__ == "__main__":
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