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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9662182 * clean up test level
60 lines
2.6 KiB
Python
60 lines
2.6 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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from modelscope.hub.snapshot_download import snapshot_download
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from modelscope.models import Model
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from modelscope.models.nlp import SbertForSequenceClassification
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from modelscope.pipelines import pipeline
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from modelscope.pipelines.nlp import PairSentenceClassificationPipeline
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from modelscope.preprocessors import PairSentenceClassificationPreprocessor
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from modelscope.utils.constant import Tasks
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from modelscope.utils.test_utils import test_level
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class SentenceSimilarityTest(unittest.TestCase):
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model_id = 'damo/nlp_structbert_sentence-similarity_chinese-base'
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sentence1 = '今天气温比昨天高么？'
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sentence2 = '今天湿度比昨天高么？'
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run(self):
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cache_path = snapshot_download(self.model_id)
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tokenizer = PairSentenceClassificationPreprocessor(cache_path)
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model = SbertForSequenceClassification.from_pretrained(cache_path)
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pipeline1 = PairSentenceClassificationPipeline(
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model, preprocessor=tokenizer)
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pipeline2 = pipeline(
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Tasks.sentence_similarity, model=model, preprocessor=tokenizer)
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print('test1')
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print(f'sentence1: {self.sentence1}\nsentence2: {self.sentence2}\n'
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f'pipeline1:{pipeline1(input=(self.sentence1, self.sentence2))}')
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print()
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print(
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f'sentence1: {self.sentence1}\nsentence2: {self.sentence2}\n'
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f'pipeline1: {pipeline2(input=(self.sentence1, self.sentence2))}')
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_with_model_from_modelhub(self):
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model = Model.from_pretrained(self.model_id)
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tokenizer = PairSentenceClassificationPreprocessor(model.model_dir)
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pipeline_ins = pipeline(
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task=Tasks.sentence_similarity,
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model=model,
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preprocessor=tokenizer)
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print(pipeline_ins(input=(self.sentence1, self.sentence2)))
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_with_model_name(self):
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pipeline_ins = pipeline(
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task=Tasks.sentence_similarity, model=self.model_id)
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print(pipeline_ins(input=(self.sentence1, self.sentence2)))
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_with_default_model(self):
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pipeline_ins = pipeline(task=Tasks.sentence_similarity)
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print(pipeline_ins(input=(self.sentence1, self.sentence2)))
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if __name__ == '__main__':
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unittest.main()
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