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Follow-up for Fixing SSIM Test Method Names #8750

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Follow-up for Fixing SSIM Test Method Names #8750

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6 changes: 3 additions & 3 deletions tests/metrics/test_ssim_metric.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@

class TestSSIMMetric(unittest.TestCase):

def test2d_gaussian(self):
def test_2d_gaussian(self):
set_determinism(0)
preds = torch.abs(torch.randn(2, 3, 16, 16))
target = torch.abs(torch.randn(2, 3, 16, 16))
Expand All @@ -34,7 +34,7 @@ def test2d_gaussian(self):
expected_value = 0.045415
self.assertTrue(expected_value - result.item() < 0.000001)
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@coderabbitai coderabbitai bot Feb 22, 2026

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⚠️ Potential issue | 🟡 Minor

One-sided tolerance check — upper-bound errors pass silently.

expected_value - result.item() < 0.000001 only fails when the result is too low; any result above expected_value trivially satisfies it. Use abs() or assertAlmostEqual.

🐛 Proposed fix (shown for line 35; apply identically to lines 48 and 61) 
-        self.assertTrue(expected_value - result.item() < 0.000001)
+        self.assertAlmostEqual(result.item(), expected_value, places=5)

Also applies to: 48-48, 61-61

🤖 Prompt for AI Agents 
Verify each finding against the current code and only fix it if needed.

In `@tests/metrics/test_ssim_metric.py` at line 35, The assertion uses a one-sided
check (expected_value - result.item() < 0.000001) which allows results greater
than expected_value to pass; replace it with a symmetric tolerance check by
using abs(expected_value - result.item()) < 1e-6 or unittest's
self.assertAlmostEqual(result.item(), expected_value, places=6) for the
assertions that reference expected_value and result.item() (apply the same
change to the other two occurrences mentioned).


def test2d_uniform(self):
def test_2d_uniform(self):
set_determinism(0)
preds = torch.abs(torch.randn(2, 3, 16, 16))
target = torch.abs(torch.randn(2, 3, 16, 16))
Expand All @@ -47,7 +47,7 @@ def test2d_uniform(self):
expected_value = 0.050103
self.assertTrue(expected_value - result.item() < 0.000001)

def test3d_gaussian(self):
def test_3d_gaussian(self):
set_determinism(0)
preds = torch.abs(torch.randn(2, 3, 16, 16, 16))
target = torch.abs(torch.randn(2, 3, 16, 16, 16))
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