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c59833c7ee
* add test level support * update develop doc Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9021354
117 lines
4.6 KiB
Python
117 lines
4.6 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import shutil
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import unittest
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import zipfile
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from pathlib import Path
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from modelscope.fileio import File
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from modelscope.models import Model
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from modelscope.models.nlp import BertForSequenceClassification
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from modelscope.pipelines import SequenceClassificationPipeline, pipeline
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from modelscope.preprocessors import SequenceClassificationPreprocessor
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from modelscope.pydatasets import PyDataset
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from modelscope.utils.constant import Hubs, Tasks
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from modelscope.utils.hub import get_model_cache_dir
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from modelscope.utils.test_utils import test_level
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class SequenceClassificationTest(unittest.TestCase):
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def setUp(self) -> None:
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self.model_id = 'damo/bert-base-sst2'
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# switch to False if downloading everytime is not desired
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purge_cache = True
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if purge_cache:
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shutil.rmtree(
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get_model_cache_dir(self.model_id), ignore_errors=True)
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def predict(self, pipeline_ins: 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_ins(data[0])
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print(results)
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results = pipeline_ins(data[1])
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print(results)
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print(data)
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def printDataset(self, dataset: PyDataset):
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for i, r in enumerate(dataset):
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if i > 10:
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break
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print(r)
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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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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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cache_path_str = r'.cache/easynlp/bert-base-sst2.zip'
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cache_path = Path(cache_path_str)
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if not cache_path.exists():
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cache_path.parent.mkdir(parents=True, exist_ok=True)
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cache_path.touch(exist_ok=True)
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with cache_path.open('wb') as ofile:
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ofile.write(File.read(model_url))
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with zipfile.ZipFile(cache_path_str, 'r') as zipf:
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zipf.extractall(cache_path.parent)
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path = r'.cache/easynlp/'
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model = BertForSequenceClassification(path)
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preprocessor = SequenceClassificationPreprocessor(
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path, first_sequence='sentence', second_sequence=None)
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pipeline1 = SequenceClassificationPipeline(model, preprocessor)
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self.predict(pipeline1)
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pipeline2 = pipeline(
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Tasks.text_classification, model=model, preprocessor=preprocessor)
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print(pipeline2('Hello world!'))
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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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preprocessor = SequenceClassificationPreprocessor(
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model.model_dir, first_sequence='sentence', second_sequence=None)
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pipeline_ins = pipeline(
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task=Tasks.text_classification,
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model=model,
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preprocessor=preprocessor)
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self.predict(pipeline_ins)
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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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text_classification = pipeline(
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task=Tasks.text_classification, model=self.model_id)
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result = text_classification(
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PyDataset.load(
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'glue', name='sst2', target='sentence', hub=Hubs.huggingface))
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self.printDataset(result)
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@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
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def test_run_with_default_model(self):
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text_classification = pipeline(task=Tasks.text_classification)
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result = text_classification(
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PyDataset.load(
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'glue', name='sst2', target='sentence', hub=Hubs.huggingface))
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self.printDataset(result)
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@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
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def test_run_with_dataset(self):
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model = Model.from_pretrained(self.model_id)
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preprocessor = SequenceClassificationPreprocessor(
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model.model_dir, first_sequence='sentence', second_sequence=None)
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text_classification = pipeline(
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Tasks.text_classification, model=model, preprocessor=preprocessor)
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# loaded from huggingface dataset
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# TODO: rename parameter as dataset_name and subset_name
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dataset = PyDataset.load(
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'glue', name='sst2', target='sentence', hub=Hubs.huggingface)
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result = text_classification(dataset)
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self.printDataset(result)
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if __name__ == '__main__':
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unittest.main()
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