47 lines
2.9 KiB
Python
47 lines
2.9 KiB
Python
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"""Opt-in operational fixtures using staged real Google weights, CPU only."""
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import io
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import math
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import os
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import unittest
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import wave
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from engine import get_model,embedding_features,inspect_content,cosine
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from semantic import validate_vectors,DIMENSIONS
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@unittest.skipUnless(os.environ.get('SAFETYNET_TEST_NATIVE_SEMANTIC')=='1','Opt in to verified native CPU fixtures')
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class NativeCPUFixtures(unittest.TestCase):
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@classmethod
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def setUpClass(cls):cls.model=get_model()
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@classmethod
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def tearDownClass(cls):cls.model.close()
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def test_real_paraphrase_blocks_and_unrelated_text_allows(self):
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reference=embedding_features(b'Our confidential launch plan schedules the new product announcement for next October.')
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protected=b'The secret product rollout will be announced in October next year.'
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public=b'The public cafeteria menu includes tomato soup and bread.'
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related=embedding_features(protected);unrelated=embedding_features(public)
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self.assertGreater(cosine(reference['vector'],related['vector']),.8)
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self.assertLess(cosine(reference['vector'],unrelated['vector']),.8)
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policy={'dlp':{'maxBytes':1048576,'rules':[],'semantic':{**self.model.info(),'enabled':True,'categories':[{'id':'native-reference','prototype':reference['vector'],'prototypes':reference['vectors'],'threshold':.8}]}}}
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self.assertEqual(inspect_content(protected,policy)['ruleId'],'native-reference')
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self.assertEqual(inspect_content(public,policy)['decision'],'allow')
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def test_native_token_windows_cover_long_document_tail(self):
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text='Public synthetic office lunch menu and team meeting schedule. '*600+'Final unique coverage marker.'
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result=embedding_features(text.encode())
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self.assertGreater(result['coverage']['textChunks'],1)
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self.assertTrue(result['coverage']['complete']);validate_vectors(result['vectors'])
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def test_native_image_encoder_returns_real_normalized_vector(self):
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from PIL import Image,ImageDraw
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image=Image.new('RGB',(192,192),'white');draw=ImageDraw.Draw(image)
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draw.rectangle((20,20,90,170),fill='blue');draw.ellipse((110,50,175,115),fill='red')
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output=io.BytesIO();image.save(output,format='PNG')
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vectors=self.model.image_vectors(output.getvalue())
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self.assertEqual(len(vectors),1);validate_vectors(vectors)
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def test_native_audio_encoder_returns_real_normalized_vector(self):
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import numpy as np
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samples=(np.sin(np.arange(16000)*2*math.pi*440/16000)*12000).astype('<i2')
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output=io.BytesIO()
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with wave.open(output,'wb') as stream:
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stream.setnchannels(1);stream.setsampwidth(2);stream.setframerate(16000);stream.writeframes(samples.tobytes())
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vectors=self.model.audio_vectors(output.getvalue())
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self.assertEqual(len(vectors),1);validate_vectors(vectors)
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if __name__=='__main__':unittest.main()
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