Salvatore Sanfilippo
0e9cc2d43e
Use the model-defined 2051-token dense boundary, handle padded selections, and synchronize reused reduction storage in Metal, CUDA and ROCm, including vision normalization. Enable bounded ROCm selected-attention GEMM for GLM 5.3 without RoPE. Add independent attention references, boundary tests and finite, repeatable vision checks. Focused Strix continued prefill improves from about 21 to 68 tokens per second; stored official scores are unchanged.
37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
"""The quality gate must reject corrupt references as well as outputs."""
|
|
|
|
import array
|
|
import pathlib
|
|
import subprocess
|
|
import sys
|
|
import tempfile
|
|
import unittest
|
|
|
|
|
|
class VisionComparisonTest(unittest.TestCase):
|
|
def compare(self, reference, candidate):
|
|
with tempfile.TemporaryDirectory() as directory:
|
|
paths = [pathlib.Path(directory) / name for name in ('ref', 'out')]
|
|
for path, values in zip(paths, (reference, candidate)):
|
|
path.write_bytes(array.array('f', values).tobytes())
|
|
return subprocess.run(
|
|
[sys.executable,
|
|
str(pathlib.Path(__file__).with_name('compare_glm53_vision_embeddings.py')),
|
|
*map(str, paths)], capture_output=True, text=True).returncode
|
|
|
|
def test_equal(self):
|
|
self.assertEqual(self.compare([1, 2, 3], [1, 2, 3]), 0)
|
|
|
|
def test_invalid(self):
|
|
for bad in ([float('nan'), 2, 3], [float('inf'), 2, 3], [0, 0, 0], []):
|
|
with self.subTest(values=bad):
|
|
self.assertNotEqual(self.compare(bad, [1, 2, 3]), 0)
|
|
self.assertNotEqual(self.compare([1, 2, 3], bad), 0)
|
|
|
|
def test_different(self):
|
|
self.assertNotEqual(self.compare([1, 2, 3], [-1, -2, -3]), 0)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|