mirror of
https://github.com/modelscope/modelscope.git
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add init
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@@ -4,3 +4,4 @@ from .sbert_for_sentence_similarity import * # noqa F403
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from .sbert_for_token_classification import * # noqa F403
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from .space.dialog_intent_prediction_model import * # noqa F403
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from .space.dialog_modeling_model import * # noqa F403
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from .space.dialog_state_tracking import * # noqa F403
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@@ -2,5 +2,6 @@ from .sentence_similarity_pipeline import * # noqa F403
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from .sequence_classification_pipeline import * # noqa F403
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from .space.dialog_intent_prediction_pipeline import * # noqa F403
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from .space.dialog_modeling_pipeline import * # noqa F403
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from .space.dialog_state_tracking import * # noqa F403
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from .text_generation_pipeline import * # noqa F403
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from .word_segmentation_pipeline import * # noqa F403
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@@ -8,4 +8,5 @@ from .image import LoadImage, load_image
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from .nlp import * # noqa F403
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from .space.dialog_intent_prediction_preprocessor import * # noqa F403
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from .space.dialog_modeling_preprocessor import * # noqa F403
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from .space.dialog_state_tracking_preprocessor import * # noqa F403
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from .text_to_speech import * # noqa F403
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@@ -0,0 +1,61 @@
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# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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from maas_hub.snapshot_download import snapshot_download
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from modelscope.models import Model
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from modelscope.models.nlp import DialogStateTrackingModel
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from modelscope.pipelines import DialogStateTrackingPipeline, pipeline
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from modelscope.preprocessors import DialogStateTrackingPreprocessor
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from modelscope.utils.constant import Tasks
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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.skip('test with snapshot_download')
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def test_run(self):
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cache_path = snapshot_download(self.model_id)
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preprocessor = DialogIntentPredictionPreprocessor(model_dir=cache_path)
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model = DialogIntentModel(
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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.dialog_intent_prediction,
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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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def test_run_with_model_from_modelhub(self):
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# model = Model.from_pretrained(self.model_id)
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# preprocessor = DialogIntentPredictionPreprocessor(
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# model_dir=model.model_dir)
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#
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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.dialog_intent_prediction,
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# model=model,
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# preprocessor=preprocessor)
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# ]
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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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pass
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if __name__ == '__main__':
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unittest.main()
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