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Use torch.testing.test_close instead of torch.testing.test_allclose (#164539)

Browse Source 
Because torch.testing.test_allclose is deprecated.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164539
Approved by: https://github.com/mlazos
This commit is contained in:
Yuanyuan Chen
2025-10-03 14:39:10 +00:00
committed by PyTorch MergeBot
parent aed66248a0
commit 5743d731c1
4 changed files with 7 additions and 7 deletions
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8
test/distributed/optim/test_apply_optimizer_in_backward.py
View File

@ -39,7 +39,7 @@ class ApplyOverlappedOptimizerTest(unittest.TestCase):
with self.subTest(i):
_validate_params(
[model.parameters() for model in models],
torch.testing.assert_allclose,
torch.testing.assert_close,
)
for opt in optimizers:
@ -77,7 +77,7 @@ class ApplyOverlappedOptimizerTest(unittest.TestCase):
model.parameters(),
model_with_opt_in_bwd.parameters(),
],
torch.testing.assert_allclose,
torch.testing.assert_close,
)
self._run_training_loop_and_validate(
@ -113,10 +113,10 @@ class ApplyOverlappedOptimizerTest(unittest.TestCase):
for p1, p2 in zip(model_with_hook.parameters(), initial_model.parameters()):
with self.assertRaises(AssertionError):
torch.testing.assert_allclose(p1, p2)
torch.testing.assert_close(p1, p2)
for p1, p2 in zip(model_no_hook.parameters(), initial_model.parameters()):
torch.testing.assert_allclose(p1, p2)
torch.testing.assert_close(p1, p2)
def test_multiple_optim_for_params(self) -> None:
model = nn.Sequential(nn.Linear(10, 10), nn.Linear(10, 10))

2
test/dynamo/test_compiler_bisector.py
View File

@ -218,7 +218,7 @@ class TestCompilerBisector(TestCase):
torch._dynamo.reset()
try:
torch.testing.assert_allclose(torch.compile(op)(x), op(x))
torch.testing.assert_close(torch.compile(op)(x), op(x))
except Exception:
return False
return True

2
test/inductor/test_config.py
View File

@ -115,7 +115,7 @@ class TestInductorConfig(TestCase):
for kwargs in checks:
torch._dynamo.reset()
opt_fn = torch.compile(dummy_fn, **kwargs)
torch.testing.assert_allclose(
torch.testing.assert_close(
opt_fn(x), y, msg=f"torch.compile(..., **{kwargs!r}) failed"
)

2
test/quantization/core/test_workflow_ops.py
View File

@ -724,7 +724,7 @@ class TestFakeQuantizeOps(TestCase):
X.cpu(), scale.cpu(), zero_point.cpu(), axis, quant_min, quant_max)
Y_prime = torch.fake_quantize_per_channel_affine(
X, scale, zero_point, axis, quant_min, quant_max)
torch.testing.assert_allclose(Y, Y_prime.cpu(), rtol=tolerance, atol=tolerance)
torch.testing.assert_close(Y, Y_prime.cpu(), rtol=tolerance, atol=tolerance)
self.assertTrue(Y.dtype == float_type)
def test_forward_per_channel_cachemask_cpu(self):