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74 lines
2.7 KiB
Python
74 lines
2.7 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 SpaceForDialogIntent
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from modelscope.pipelines import pipeline
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from modelscope.pipelines.nlp import DialogIntentPredictionPipeline
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from modelscope.preprocessors import DialogIntentPredictionPreprocessor
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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 DialogIntentPredictionTest(unittest.TestCase):
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model_id = 'damo/nlp_space_dialog-intent-prediction'
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test_case = [
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'How do I locate my card?',
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'I still have not received my new card, I ordered over a week ago.'
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]
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@unittest.skipUnless(test_level() >= 2, '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, revision='update')
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preprocessor = DialogIntentPredictionPreprocessor(model_dir=cache_path)
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model = SpaceForDialogIntent(
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model_dir=cache_path,
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text_field=preprocessor.text_field,
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config=preprocessor.config)
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pipelines = [
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DialogIntentPredictionPipeline(
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model=model, preprocessor=preprocessor),
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pipeline(
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task=Tasks.task_oriented_conversation,
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model=model,
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preprocessor=preprocessor)
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]
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for my_pipeline, item in list(zip(pipelines, self.test_case)):
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print(my_pipeline(item))
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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, revision='update')
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preprocessor = DialogIntentPredictionPreprocessor(
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model_dir=model.model_dir)
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pipelines = [
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DialogIntentPredictionPipeline(
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model=model, preprocessor=preprocessor),
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pipeline(
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task=Tasks.task_oriented_conversation,
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model=model,
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preprocessor=preprocessor)
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]
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for my_pipeline, item in list(zip(pipelines, self.test_case)):
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print(my_pipeline(item))
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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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pipelines = [
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pipeline(
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task=Tasks.task_oriented_conversation,
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model=self.model_id,
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model_revision='update')
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]
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for my_pipeline, item in list(zip(pipelines, self.test_case)):
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print(my_pipeline(item))
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if __name__ == '__main__':
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unittest.main()
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