saymrwulf/pytorch
1
0
Fork 0
mirror of https://github.com/saymrwulf/pytorch.git synced 2026-05-14 20:57:59 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

fix tf32 issue in test_inductor_freezing.py unit tests (#146444)

Browse source 
Test is hitting numerical mismatches in NVIDIA internal CI. Add tf32_on_and_off decorater, update check to assertEqual

Pull Request resolved: https://github.com/pytorch/pytorch/pull/146444
Approved by: https://github.com/jansel, https://github.com/eellison, https://github.com/eqy
This commit is contained in:
Fuzzkatt 2025-02-06 23:34:26 +00:00 committed by PyTorch MergeBot
parent 7bd7f735d4
commit e13a544b54
1 changed files with 4 additions and 5 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

9
test/inductor/test_inductor_freezing.py
View file

@ -15,7 +15,7 @@ from torch._inductor import config
from torch._inductor.test_case import TestCase as InductorTestCase
from torch._inductor.utils import override_lowering, run_and_get_code
from torch.testing import FileCheck
from torch.testing._internal.common_cuda import SM80OrLater
from torch.testing._internal.common_cuda import SM80OrLater, tf32_on_and_off
from torch.testing._internal.common_utils import IS_FBCODE, skipIfRocm, skipIfXpu
@ -770,6 +770,7 @@ class OptimizeForInferenceTemplate(TestCase):
self.assertEqual(foo(mod, x), out_eager)
self.assertEqual(foo(mod, x), out_eager)
@tf32_on_and_off(0.001)
def test_conv_layout_convert_with_view(self):
class Model(torch.nn.Module):
def __init__(self) -> None:
@ -887,6 +888,7 @@ class OptimizeForInferenceTemplate(TestCase):
self.assertEqual(out_eager, out_compiled)
@skipIfRocm
@tf32_on_and_off(0.001)
def test_redundant_clone_for_layout_convert(self):
class Model(torch.nn.Module):
def __init__(self) -> None:
@ -932,10 +934,7 @@ class OptimizeForInferenceTemplate(TestCase):
for i, actual, expected in zip(
itertools.count(), actual_outputs, expected_outputs
):
self.assertTrue(
torch.allclose(expected, actual, atol=1e-4, rtol=1e-4),
f"{i}th output: expected {expected}, actual {actual}",
)
self.assertEqual(expected, actual)
if self.device == "cpu":
# CPU use different convolution implementation, skip the checks below