mirror of
https://github.com/modelscope/modelscope.git
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58 lines
2.5 KiB
Python
58 lines
2.5 KiB
Python
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# 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 TransformerCRFForWordSegmentation
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from modelscope.pipelines import pipeline
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from modelscope.pipelines.nlp import WordSegmentationThaiPipeline
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from modelscope.preprocessors import WordSegmentationPreprocessorThai
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from modelscope.utils.constant import Tasks
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from modelscope.utils.demo_utils import DemoCompatibilityCheck
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from modelscope.utils.regress_test_utils import MsRegressTool
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from modelscope.utils.test_utils import test_level
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class WordSegmentationTest(unittest.TestCase, DemoCompatibilityCheck):
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def setUp(self) -> None:
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self.task = Tasks.word_segmentation
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self.model_id = 'damo/nlp_xlmr_word-segmentation_thai'
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sentence = 'รถคันเก่าก็ยังเก็บเอาไว้ยังไม่ได้ขาย'
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regress_tool = MsRegressTool(baseline=False)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_by_direct_model_download(self):
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cache_path = snapshot_download(self.model_id)
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tokenizer = WordSegmentationPreprocessorThai(cache_path)
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model = TransformerCRFForWordSegmentation.from_pretrained(cache_path)
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pipeline1 = WordSegmentationThaiPipeline(model, preprocessor=tokenizer)
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pipeline2 = pipeline(
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Tasks.word_segmentation, model=model, preprocessor=tokenizer)
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print(f'sentence: {self.sentence}\n'
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f'pipeline1:{pipeline1(input=self.sentence)}')
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print(f'pipeline2: {pipeline2(input=self.sentence)}')
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@unittest.skipUnless(test_level() >= 0, '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 = WordSegmentationPreprocessorThai(model.model_dir)
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pipeline_ins = pipeline(
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task=Tasks.word_segmentation, model=model, preprocessor=tokenizer)
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print(pipeline_ins(input=self.sentence))
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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.word_segmentation, model=self.model_id)
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print(pipeline_ins(input=self.sentence))
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@unittest.skip('demo compatibility test is only enabled on a needed-basis')
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def test_demo_compatibility(self):
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self.compatibility_check()
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if __name__ == '__main__':
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unittest.main()
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