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[Break XPU] Fix XPU UT failures introduced by community. (#156091)

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Fixes #15089, Fixes #156063, Fixes #155689, Fixes #155692, Fixes #156146

Pull Request resolved: https://github.com/pytorch/pytorch/pull/156091
Approved by: https://github.com/jansel
This commit is contained in:
xinan.lin
2025-06-16 14:30:20 -07:00
committed by PyTorch MergeBot
parent 38e1e5d54c
commit 3dabc351bb
4 changed files with 5 additions and 5 deletions
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6
test/dynamo/test_precompile_context.py
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@ -11,7 +11,7 @@ from torch._functorch._aot_autograd.autograd_cache import (
BundledAOTAutogradCacheEntry,
)
from torch._inductor.test_case import TestCase as InductorTestCase
from torch.testing._internal.inductor_utils import requires_triton
from torch.testing._internal.inductor_utils import GPU_TYPE, requires_triton
@functorch_config.patch({"enable_autograd_cache": True})
@ -39,7 +39,7 @@ class PrecompileContextTests(InductorTestCase):
compiled_fn = torch.compile(simple_function)
# Run the compiled function
x = torch.randn(10, device="cuda", requires_grad=True)
x = torch.randn(10, device=GPU_TYPE, requires_grad=True)
result = compiled_fn(x)
result.sum().backward()
# Check that PrecompileContext._new_cache_artifacts_by_key has length 1
@ -80,7 +80,7 @@ class PrecompileContextTests(InductorTestCase):
compiled_fn = torch.compile(simple_function)
# Run the compiled function
x = torch.randn(10, device="cuda", requires_grad=True)
x = torch.randn(10, device=GPU_TYPE, requires_grad=True)
result = compiled_fn(x)
result.sum().backward()
# Check that PrecompileContext._new_cache_artifacts_by_key has length 1

1
test/inductor/test_torchinductor_codegen_dynamic_shapes.py
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@ -242,7 +242,6 @@ test_failures = {
"test_pointwise_laguerre_polynomial_l_dynamic_shapes": TestFailure(("cuda", "xpu")),
"test_pointwise_legendre_polynomial_p_dynamic_shapes": TestFailure(("cuda", "xpu")),
"test_polar_dynamic_shapes": TestFailure(("cpu", "cuda", "xpu"), is_skip=True),
"test_randint_distribution_dynamic_shapes": TestFailure(("cuda", "xpu")),
"test_randn_generator_dynamic_shapes": TestFailure(("cpu",)),
"test_randn_like_empty_dynamic_shapes": TestFailure(("cpu", "cuda", "xpu")),
"test_single_elem_dynamic_shapes": TestFailure(("cpu",)),

1
test/inductor/test_torchinductor_dynamic_shapes.py
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@ -61,7 +61,6 @@ test_failures = {
"test_AllenaiLongformerBase_repro_dynamic_shapes": TestFailure(
("cpu", "cuda", "xpu")
),
"test_randint_distribution_dynamic_shapes": TestFailure(("xpu",)),
}
if not torch._inductor.config.cpp_wrapper:
test_failures["test_conv_inference_heuristics_dynamic_shapes"] = TestFailure(

2
test/test_openreg.py
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@ -13,6 +13,7 @@ from torch.testing._internal.common_utils import (
IS_LINUX,
run_tests,
skipIfTorchDynamo,
skipIfXpu,
TestCase,
)
@ -365,6 +366,7 @@ class TestOpenReg(TestCase):
self.assertEqual(y.to(device="cpu"), torch.tensor([[1, 1], [2, 2], [3, 3]]))
self.assertEqual(x.data_ptr(), y.data_ptr())
@skipIfXpu(msg="missing kernel for openreg")
def test_quantize(self):
x = torch.randn(3, 4, 5, dtype=torch.float32, device="openreg")
quantized_tensor = torch.quantize_per_tensor(x, 0.1, 10, torch.qint8)