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[ROCm][CI] unskip some test_memory_format tests (#162766)

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Fixes #70125.

Much of the work was done by #161687.
This PR is additional test cleanup.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162766
Approved by: https://github.com/jeffdaily

Co-authored-by: Jeff Daily <jeff.daily@amd.com>
This commit is contained in:
Jeff Daily
2025-09-12 15:02:40 +00:00
committed by PyTorch MergeBot
parent 03798b0f91
commit 7357eb66c5
2 changed files with 8 additions and 29 deletions
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8
test/test_modules.py
View File

@ -15,10 +15,16 @@ from torch.testing._internal.common_device_type import (
from torch.testing._internal.common_modules import module_db, modules, ModuleErrorEnum, TrainEvalMode
from torch.testing._internal.common_utils import (
TestCase, run_tests, freeze_rng_state, mock_wrapper, get_tensors_from, gradcheck,
gradgradcheck, parametrize, wrapSwapTensorsTest)
gradgradcheck, parametrize, wrapSwapTensorsTest, TEST_WITH_ROCM)
from unittest.mock import patch, call
if TEST_WITH_ROCM:
import os
os.environ["PYTORCH_MIOPEN_SUGGEST_NHWC"] = "1"
os.environ["PYTORCH_MIOPEN_SUGGEST_NHWC_BATCHNORM"] = "1"
class TestModule(TestCase):
_do_cuda_memory_leak_check = True
_do_cuda_non_default_stream = True

29
torch/testing/_internal/common_modules.py
View File

@ -16,7 +16,7 @@ from torch.testing._internal.common_dtype import (
floating_types, floating_and_complex_types_and, get_all_fp_dtypes)
from torch.testing._internal.common_device_type import (
_TestParametrizer, _update_param_kwargs, expectedFailureMPS, toleranceOverride, tol,
skipCUDAIfRocm, precisionOverride, skipMeta, skipMPS)
precisionOverride, skipMeta, skipMPS)
from torch.testing._internal.common_methods_invocations import DecorateInfo
from torch.testing._internal.common_nn import (
cosineembeddingloss_reference, cross_entropy_loss_reference, ctcloss_reference,
@ -3497,8 +3497,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# See #119108: MPSNDArrayConvolutionA14.mm:3976: failed assertion `destination datatype must be fp32'
# xfail does not work due to Fatal Python error: Aborted
DecorateInfo(skipIfMPSOnMacOS13, "TestModule", "test_memory_format",
@ -3514,8 +3512,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# This was wrongly being skipped before and needs investigation.
# See https://github.com/pytorch/pytorch/issues/80247
DecorateInfo(unittest.expectedFailure, "TestModule", "test_memory_format",
@ -3538,8 +3534,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Conv3d is not supported on MPS backend
DecorateInfo(skipMPS, device_type="mps"),
# This was wrongly being skipped before and needs investigation.
@ -3555,8 +3549,6 @@ module_db: list[ModuleInfo] = [
module_memformat_affects_out=True,
dtypes=floating_and_complex_types_and(torch.chalf),
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Not implemented for chalf on CPU
DecorateInfo(unittest.expectedFailure, 'TestModule', 'test_cpu_gpu_parity',
dtypes=(torch.chalf,), device_type='cuda'),
@ -3576,8 +3568,6 @@ module_db: list[ModuleInfo] = [
module_memformat_affects_out=True,
dtypes=floating_and_complex_types_and(torch.chalf),
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Fails on backward check because ViewAsRealBackward apply contiguous for grad
DecorateInfo(unittest.expectedFailure, 'TestModule', 'test_memory_format',
dtypes=(torch.complex32, torch.complex64, torch.complex128)),
@ -3608,16 +3598,11 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# ConvTranspose3d is not supported on MPS backend
DecorateInfo(skipMPS),
# This was wrongly being skipped before and needs investigation.
# See https://github.com/pytorch/pytorch/issues/80247
DecorateInfo(unittest.expectedFailure, "TestModule", "test_memory_format"),
# These fail only on ROCm
DecorateInfo(unittest.expectedFailure, "TestModule", "test_memory_format", device_type='cuda',
dtypes=[torch.complex32, torch.complex64], active_if=TEST_WITH_ROCM),
# Not implemented for chalf on CPU
DecorateInfo(unittest.expectedFailure, 'TestModule', 'test_cpu_gpu_parity',
dtypes=(torch.chalf,), device_type='cuda'),
@ -3677,8 +3662,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Lazy modules don't currently play well with ModuleInfo tests on the meta device.
# See https://github.com/pytorch/pytorch/issues/70505 for more info.
DecorateInfo(skipMeta),
@ -3697,8 +3680,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Lazy modules don't currently play well with ModuleInfo tests on the meta device.
# See https://github.com/pytorch/pytorch/issues/70505 for more info.
DecorateInfo(skipMeta),
@ -3724,8 +3705,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Lazy modules don't currently play well with ModuleInfo tests on the meta device.
# See https://github.com/pytorch/pytorch/issues/70505 for more info.
DecorateInfo(skipMeta),
@ -3743,8 +3722,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Lazy modules don't currently play well with ModuleInfo tests on the meta device.
# See https://github.com/pytorch/pytorch/issues/70505 for more info.
DecorateInfo(skipMeta),
@ -3763,8 +3740,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Lazy modules don't currently play well with ModuleInfo tests on the meta device.
# See https://github.com/pytorch/pytorch/issues/70505 for more info.
DecorateInfo(skipMeta),
@ -3790,8 +3765,6 @@ module_db: list[ModuleInfo] = [
gradcheck_nondet_tol=GRADCHECK_NONDET_TOL,
module_memformat_affects_out=True,
skips=(
# Failure on ROCM for float32 issue #70125
DecorateInfo(skipCUDAIfRocm, 'TestModule', 'test_memory_format', dtypes=[torch.float32]),
# Lazy modules don't currently play well with ModuleInfo tests on the meta device.
# See https://github.com/pytorch/pytorch/issues/70505 for more info.
DecorateInfo(skipMeta),