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158d72bfd2
* add self supervised depth completion. * update. * fix the problem of key inconsistency. * delete args parser. * rename metrics to test_metrics.
45 lines
1.2 KiB
Python
45 lines
1.2 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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import numpy as np
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from modelscope.metrics.token_classification_metric import \
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TokenClassificationMetric
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from modelscope.utils.test_utils import test_level
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class TestTokenClsMetrics(unittest.TestCase):
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_value(self):
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metric = TokenClassificationMetric()
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class Trainer:
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pass
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metric.trainer = Trainer()
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metric.trainer.label2id = {
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'B-obj': 0,
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'I-obj': 1,
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'O': 2,
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}
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outputs = {
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'logits':
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np.array([[[2.0, 1.0, 0.5], [1.0, 1.5, 1.0], [2.0, 1.0, 3.0],
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[2.4, 1.5, 4.0], [2.0, 1.0, 3.0], [2.4, 1.5, 1.7],
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[2.0, 1.0, 0.5], [2.4, 1.5, 0.5]]])
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}
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inputs = {'labels': np.array([[0, 1, 2, 2, 0, 1, 2, 2]])}
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metric.add(outputs, inputs)
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ret = metric.evaluate()
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self.assertTrue(np.isclose(ret['precision'], 0.25))
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self.assertTrue(np.isclose(ret['recall'], 0.5))
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self.assertTrue(np.isclose(ret['accuracy'], 0.5))
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print(ret)
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if __name__ == '__main__':
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unittest.main()
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