Remove old ROCm version check in tests (#164245)

This PR removes ROCm<6 version checks.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164245
Approved by: https://github.com/jeffdaily
This commit is contained in:
Yuanyuan Chen 2025-10-06 22:42:01 +00:00 committed by PyTorch MergeBot
parent 3912ba3e94
commit b63bbe1661
4 changed files with 2 additions and 15 deletions

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@ -38,7 +38,6 @@ from torch.testing._internal.common_utils import (
gradcheck, gradcheck,
parametrize, parametrize,
run_tests, run_tests,
skipIfRocmVersionLessThan,
skipIfTorchDynamo, skipIfTorchDynamo,
TEST_WITH_ROCM, TEST_WITH_ROCM,
TestCase, TestCase,
@ -196,7 +195,6 @@ class TestForeach(TestCase):
zero_size=True, zero_size=True,
) )
@skipIfRocmVersionLessThan((6, 0))
@ops( @ops(
foreach_unary_op_db foreach_unary_op_db
+ foreach_binary_op_db + foreach_binary_op_db

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@ -29,8 +29,7 @@ from torch.testing._internal.common_device_type import \
(instantiate_device_type_tests, dtypes, has_cusolver, has_hipsolver, (instantiate_device_type_tests, dtypes, has_cusolver, has_hipsolver,
onlyCPU, skipCUDAIfNoMagma, skipCPUIfNoLapack, precisionOverride, onlyCPU, skipCUDAIfNoMagma, skipCPUIfNoLapack, precisionOverride,
skipCUDAIfNoMagmaAndNoCusolver, skipCUDAIfRocm, onlyNativeDeviceTypes, dtypesIfCUDA, skipCUDAIfNoMagmaAndNoCusolver, skipCUDAIfRocm, onlyNativeDeviceTypes, dtypesIfCUDA,
onlyCUDA, skipMeta, skipCUDAIfNoCusolver, skipCUDAIfNotRocm, skipCUDAIfRocmVersionLessThan, onlyCUDA, skipMeta, skipCUDAIfNoCusolver, skipCUDAIfNotRocm, dtypesIfMPS, largeTensorTest)
dtypesIfMPS, largeTensorTest)
from torch.testing import make_tensor from torch.testing import make_tensor
from torch.testing._internal.common_dtype import ( from torch.testing._internal.common_dtype import (
all_types, all_types_and_complex_and, floating_and_complex_types, integral_types, all_types, all_types_and_complex_and, floating_and_complex_types, integral_types,
@ -7303,7 +7302,6 @@ scipy_lobpcg | {eq_err_scipy:10.2e} | {eq_err_general_scipy:10.2e} | {iters2:
@unittest.skipIf(IS_WINDOWS, "Skipped on Windows!") @unittest.skipIf(IS_WINDOWS, "Skipped on Windows!")
@unittest.skipIf(SM90OrLater and not TEST_WITH_ROCM, "Expected failure on sm90") @unittest.skipIf(SM90OrLater and not TEST_WITH_ROCM, "Expected failure on sm90")
@unittest.skipIf(IS_FBCODE and IS_REMOTE_GPU, "cublas runtime error") @unittest.skipIf(IS_FBCODE and IS_REMOTE_GPU, "cublas runtime error")
@skipCUDAIfRocmVersionLessThan((6, 0))
@onlyCUDA @onlyCUDA
@parametrize("k", [16, 32]) @parametrize("k", [16, 32])
@parametrize("n", [16, 32]) @parametrize("n", [16, 32])
@ -7374,7 +7372,6 @@ scipy_lobpcg | {eq_err_scipy:10.2e} | {eq_err_general_scipy:10.2e} | {iters2:
@unittest.skipIf(IS_WINDOWS, "Skipped on Windows!") @unittest.skipIf(IS_WINDOWS, "Skipped on Windows!")
@unittest.skipIf(IS_FBCODE and IS_REMOTE_GPU, "cublas runtime error") @unittest.skipIf(IS_FBCODE and IS_REMOTE_GPU, "cublas runtime error")
@skipCUDAIfRocmVersionLessThan((6, 0))
@onlyCUDA @onlyCUDA
def test__int_mm_errors(self, device): def test__int_mm_errors(self, device):

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@ -36,7 +36,6 @@ from torch.testing._internal.common_utils import (
parametrize, parametrize,
run_tests, run_tests,
skipIfRocm, skipIfRocm,
skipIfRocmVersionLessThan,
TEST_CUDA, TEST_CUDA,
TEST_WITH_ROCM, TEST_WITH_ROCM,
TestCase, TestCase,
@ -144,7 +143,6 @@ class TestMatmulCuda(InductorTestCase):
torch.backends.cuda.matmul.allow_fp16_accumulation = orig_fp16_accumulate torch.backends.cuda.matmul.allow_fp16_accumulation = orig_fp16_accumulate
@onlyCUDA @onlyCUDA
@skipIfRocmVersionLessThan((5, 2))
# imported 'tol' as 'xtol' to avoid aliasing in code above # imported 'tol' as 'xtol' to avoid aliasing in code above
@toleranceOverride({torch.float16: xtol(atol=1e-1, rtol=1e-1), @toleranceOverride({torch.float16: xtol(atol=1e-1, rtol=1e-1),
torch.bfloat16: xtol(atol=1e-1, rtol=1e-1), torch.bfloat16: xtol(atol=1e-1, rtol=1e-1),
@ -158,7 +156,6 @@ class TestMatmulCuda(InductorTestCase):
@onlyCUDA @onlyCUDA
@xfailIfSM100OrLaterAndCondition(lambda params: params.get('dtype') == torch.bfloat16 and params.get('size') == 10000) @xfailIfSM100OrLaterAndCondition(lambda params: params.get('dtype') == torch.bfloat16 and params.get('size') == 10000)
@skipIfRocmVersionLessThan((5, 2))
# imported 'tol' as 'xtol' to avoid aliasing in code above # imported 'tol' as 'xtol' to avoid aliasing in code above
@toleranceOverride({torch.float16: xtol(atol=7e-1, rtol=2e-1), @toleranceOverride({torch.float16: xtol(atol=7e-1, rtol=2e-1),
torch.bfloat16: xtol(atol=1e1, rtol=2e-1)}) torch.bfloat16: xtol(atol=1e1, rtol=2e-1)})
@ -170,7 +167,6 @@ class TestMatmulCuda(InductorTestCase):
self.cublas_addmm(size, dtype, True) self.cublas_addmm(size, dtype, True)
@onlyCUDA @onlyCUDA
@skipIfRocmVersionLessThan((5, 2))
@dtypes(torch.float16) @dtypes(torch.float16)
# m == 4 chooses OUTPUT_TYPE reduction on H200 # m == 4 chooses OUTPUT_TYPE reduction on H200
# m == 8 chooses OUTPUT_TYPE reduction on A100 # m == 8 chooses OUTPUT_TYPE reduction on A100
@ -191,7 +187,6 @@ class TestMatmulCuda(InductorTestCase):
torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = orig_precision torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = orig_precision
@onlyCUDA @onlyCUDA
@skipIfRocmVersionLessThan((5, 2))
# imported 'tol' as 'xtol' to avoid aliasing in code above # imported 'tol' as 'xtol' to avoid aliasing in code above
@toleranceOverride({torch.float16: xtol(atol=7e-1, rtol=2e-1), @toleranceOverride({torch.float16: xtol(atol=7e-1, rtol=2e-1),
torch.bfloat16: xtol(atol=1e1, rtol=2e-1)}) torch.bfloat16: xtol(atol=1e1, rtol=2e-1)})

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@ -16,8 +16,7 @@ from torch.testing._internal.common_utils import \
skipIfRocmVersionLessThan, IS_FBCODE, IS_REMOTE_GPU, suppress_warnings) skipIfRocmVersionLessThan, IS_FBCODE, IS_REMOTE_GPU, suppress_warnings)
from torch.testing._internal.common_device_type import \ from torch.testing._internal.common_device_type import \
(ops, instantiate_device_type_tests, dtypes, OpDTypes, dtypesIfCUDA, onlyCPU, onlyCUDA, skipCUDAIfNoSparseGeneric, (ops, instantiate_device_type_tests, dtypes, OpDTypes, dtypesIfCUDA, onlyCPU, onlyCUDA, skipCUDAIfNoSparseGeneric,
precisionOverride, skipMeta, skipCUDAIf, skipCUDAIfRocm, skipCPUIfNoMklSparse, skipCUDAIfRocmVersionLessThan, precisionOverride, skipMeta, skipCUDAIf, skipCUDAIfRocm, skipCPUIfNoMklSparse, largeTensorTest)
largeTensorTest)
from torch.testing._internal.common_methods_invocations import \ from torch.testing._internal.common_methods_invocations import \
(op_db, sparse_csr_unary_ufuncs, ReductionOpInfo) (op_db, sparse_csr_unary_ufuncs, ReductionOpInfo)
from torch.testing._internal.common_cuda import TEST_CUDA from torch.testing._internal.common_cuda import TEST_CUDA
@ -1492,8 +1491,6 @@ class TestSparseCSR(TestCase):
csr.matmul(bad_vec) csr.matmul(bad_vec)
@onlyCUDA @onlyCUDA
# hmm, the test passes ok on CUDA when Rocm is not available:
@skipCUDAIfRocmVersionLessThan((5, 2))
@dtypes(torch.float32, torch.float64, torch.complex64, torch.complex128) @dtypes(torch.float32, torch.float64, torch.complex64, torch.complex128)
def test_baddbmm(self, device, dtype): def test_baddbmm(self, device, dtype):