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49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
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# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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import os.path as osp
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import tempfile
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import unittest
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import zipfile
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from maas_lib.fileio import File
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from maas_lib.models.nlp import SequenceClassificationModel
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from maas_lib.pipelines import SequenceClassificationPipeline
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from maas_lib.preprocessors import SequenceClassificationPreprocessor
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class SequenceClassificationTest(unittest.TestCase):
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def predict(self, pipeline: SequenceClassificationPipeline):
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from easynlp.appzoo import load_dataset
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set = load_dataset('glue', 'sst2')
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data = set['test']['sentence'][:3]
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results = pipeline(data[0])
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print(results)
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results = pipeline(data[1])
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print(results)
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print(data)
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def test_run(self):
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model_url = 'https://atp-modelzoo-sh.oss-cn-shanghai.aliyuncs.com' \
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'/release/easynlp_modelzoo/alibaba-pai/bert-base-sst2.zip'
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with tempfile.TemporaryDirectory() as tmp_dir:
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tmp_file = osp.join(tmp_dir, 'bert-base-sst2.zip')
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with open(tmp_file, 'wb') as ofile:
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ofile.write(File.read(model_url))
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with zipfile.ZipFile(tmp_file, 'r') as zipf:
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zipf.extractall(tmp_dir)
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path = osp.join(tmp_dir, 'bert-base-sst2')
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print(path)
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model = SequenceClassificationModel(path)
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preprocessor = SequenceClassificationPreprocessor(
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path, first_sequence='sentence', second_sequence=None)
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pipeline = SequenceClassificationPipeline(model, preprocessor)
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self.predict(pipeline)
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if __name__ == '__main__':
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unittest.main()
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