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Fix several test_ops cuda dtypes tests #60922

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Fix several test_ops cuda dtypes tests #60922

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8561bcc
fix
xwang233 Jun 29, 2021
2a07f25
fix
xwang233 Jun 29, 2021
8251de7
Merge remote-tracking branch 'upstream/master' into cuda_dtypes_fix
xwang233 Jun 29, 2021
fc3426e
Merge remote-tracking branch 'upstream/master' into cuda_dtypes_fix
xwang233 Jul 1, 2021
93fd817
Merge remote-tracking branch 'upstream/master' into cuda_dtypes_fix
xwang233 Jul 6, 2021
05fca2e
SM60OrLater and CUDA11OrLater
xwang233 Jul 6, 2021
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1 change: 1 addition & 0 deletions torch/testing/_internal/common_cuda.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
CUDA11OrLater = torch.version.cuda and distutils.version.LooseVersion(torch.version.cuda) >= "11.0"
CUDA9 = torch.version.cuda and torch.version.cuda.startswith('9.')
SM53OrLater = torch.cuda.is_available() and torch.cuda.get_device_capability() >= (5, 3)
SM60OrLater = torch.cuda.is_available() and torch.cuda.get_device_capability() >= (6, 0)

TEST_MAGMA = TEST_CUDA
if TEST_CUDA:
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21 changes: 8 additions & 13 deletions torch/testing/_internal/common_methods_invocations.py
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Expand Up @@ -23,7 +23,7 @@
from torch.testing._internal.common_device_type import \
(skipIf, skipCUDAIfNoMagma, skipCUDAIfNoMagmaAndNoCusolver, skipCUDAIfNoCusolver,
skipCPUIfNoLapack, skipCPUIfNoFFT, skipCUDAIfRocm, precisionOverride, toleranceOverride, tol)
from torch.testing._internal.common_cuda import CUDA11OrLater, SM53OrLater
from torch.testing._internal.common_cuda import CUDA11OrLater, SM53OrLater, SM60OrLater
from torch.testing._internal.common_utils import \
(is_iterable_of_tensors,
random_symmetric_matrix, random_symmetric_psd_matrix,
Expand Down Expand Up @@ -6069,13 +6069,11 @@ def gradcheck_wrapper_triangular_input(op, input, *args, upper=False, **kwargs):
dtypesIfCPU=all_types_and_complex(),
dtypesIfCUDA=floating_and_complex_types_and(torch.float16, *[torch.bfloat16] if CUDA11OrLater else []),
dtypesIfROCM=floating_types_and(torch.half, torch.bfloat16),
backward_dtypesIfCUDA=floating_and_complex_types_and(torch.float16),
backward_dtypesIfCUDA=floating_and_complex_types_and(torch.float16,
*[torch.bfloat16] if (SM60OrLater and CUDA11OrLater) else []),
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ping @mruberry . Seems like the CI is happy with the new flags

assert_autodiffed=True,
sample_inputs_func=sample_inputs_matmul,
skips=(
# FIXME: bfloat16 backward support likely depends on CUDA11+
# and SM53+
SkipInfo('TestCommon', 'test_dtypes', active_if=IS_WINDOWS),
# matmul does not correctly warn when resizing out= inputs
SkipInfo('TestCommon', 'test_out'),
SkipInfo('TestCommon', 'test_conj_view', device_type='cpu'),
Expand Down Expand Up @@ -6545,14 +6543,13 @@ def gradcheck_wrapper_triangular_input(op, input, *args, upper=False, **kwargs):
dtypesIfCPU=all_types_and_complex(),
dtypesIfCUDA=floating_types_and(torch.float16, *[torch.bfloat16] if CUDA11OrLater else [],
torch.complex64, torch.complex128),
backward_dtypesIfCUDA=floating_types_and(torch.float16, torch.complex64, torch.complex128),
backward_dtypesIfCUDA=floating_types_and(torch.float16,
*[torch.bfloat16] if (SM60OrLater and CUDA11OrLater) else [],
torch.complex64, torch.complex128),
assert_autodiffed=True,
sample_inputs_func=sample_inputs_matmul,
supports_out=False,
skips=(
# FIXME: bfloat16 backward support likely depends on CUDA11+
# and SM53+
SkipInfo('TestCommon', 'test_dtypes', active_if=IS_WINDOWS),
SkipInfo('TestJit', 'test_variant_consistency_jit',),
)),
OpInfo('__rmod__',
Expand Down Expand Up @@ -6904,13 +6901,11 @@ def gradcheck_wrapper_triangular_input(op, input, *args, upper=False, **kwargs):
op=lambda tensors, equation: torch.einsum(equation, tensors),
dtypes=all_types_and_complex_and(torch.half, torch.bfloat16),
dtypesIfCUDA=floating_and_complex_types_and(torch.half, *[torch.bfloat16] if CUDA11OrLater else []),
backward_dtypesIfCUDA=floating_and_complex_types_and(torch.half),
backward_dtypesIfCUDA=floating_and_complex_types_and(torch.half,
*[torch.bfloat16] if (SM60OrLater and CUDA11OrLater) else []),
supports_out=False,
sample_inputs_func=sample_inputs_einsum,
skips=(
# FIXME: bfloat16 backward support likely depends on CUDA11+
# and SM53+
SkipInfo('TestCommon', 'test_dtypes', active_if=IS_WINDOWS),
# test does not work with passing lambda for op
# there's a test `test_einsum` in `test_jit.py` to handle this case
SkipInfo('TestJit', 'test_variant_consistency_jit'),
Expand Down