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https://github.com/MrSleeps/jellyfin-scene-search.git
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Sleeps
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
from __future__ import annotations
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import math
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from types import SimpleNamespace
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import unittest
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import numpy as np
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import torch
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from scene_search.embedder import SiglipEmbedder
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class SiglipMatchScoringTests(unittest.TestCase):
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def test_match_probabilities_use_model_scale_and_bias(self) -> None:
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embedder = SiglipEmbedder.__new__(SiglipEmbedder)
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embedder.device = torch.device("cpu")
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embedder.model = SimpleNamespace(
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logit_scale=torch.tensor(math.log(2.0)),
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logit_bias=torch.tensor(-1.0),
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)
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text = np.asarray([1.0, 0.0], dtype=np.float32)
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images = np.asarray(
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[
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[1.0, 0.0],
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[0.0, 1.0],
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],
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dtype=np.float32,
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)
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scores = embedder.match_probabilities(text, images)
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self.assertAlmostEqual(float(scores[0]), 0.7310586, places=6)
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self.assertAlmostEqual(float(scores[1]), 0.2689414, places=6)
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self.assertGreater(float(scores[0]), float(scores[1]))
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if __name__ == "__main__":
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unittest.main()
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