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Add OpInfo tests for torch.{dot, vdot, bmm, mv} (#56409)

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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/56409

Reviewed By: nikithamalgifb

Differential Revision: D27870769

Pulled By: anjali411

fbshipit-source-id: a1a0e89856529a4739c7612c5b1e3c5ed2569126
This commit is contained in:
anjali411
2021-04-20 10:20:36 -07:00
committed by Facebook GitHub Bot
parent e4faebca0d
commit 062e70590c
2 changed files with 77 additions and 10 deletions
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6
test/test_autograd.py
View File

@ -5385,10 +5385,8 @@ complex_list = ['t', 'view', 'reshape', 'reshape_as', 'view_as', 'roll', 'clone'
'expand', 'rot90', 'transpose',
'permute', 'squeeze', 'unsqueeze', 'resize', 'resize_as', 'tril', 'triu',
'chunk', 'split', 'split_with_sizes', 'zero_',
'__radd__', 'sum', 'mul',
'__rmul__', 'dot', 'vdot', 'matmul',
'bmm', 'mv', 'ger', 'diagonal', 'fill_', 'sub',
'mean', 'inverse', 'linalg.tensorinv', 'matrix_exp',
'__radd__', 'mul', '__rmul__', 'matmul',
'diagonal', 'fill_', 'sub',
'narrow', 'swapaxes', 'swapdims', 'tensor_split',
'baddbmm'] + complex_list_filter + separate_complex_tests

81
torch/testing/_internal/common_methods_invocations.py
View File

@ -658,6 +658,36 @@ def sample_inputs_addmm(op_info, device, dtype, requires_grad, **kwargs):
else:
return (input, )
def sample_inputs_mv(self, device, dtype, requires_grad, **kwargs):
return (
SampleInput(
make_tensor((S, M, ), device, dtype, low=None, high=None, requires_grad=requires_grad),
args=(
make_tensor((M, ), device, dtype, low=None, high=None, requires_grad=requires_grad),
)
),
)
def sample_inputs_bmm(self, device, dtype, requires_grad, **kwargs):
return (
SampleInput(
make_tensor((M, S, M, ), device, dtype, low=None, high=None, requires_grad=requires_grad),
args=(
make_tensor((M, M, S, ), device, dtype, low=None, high=None, requires_grad=requires_grad),
)
),
)
def sample_inputs_dot_vdot(self, device, dtype, requires_grad, **kwargs):
return (
SampleInput(
make_tensor((S, ), device, dtype, low=None, high=None, requires_grad=requires_grad),
args=(
make_tensor((S, ), device, dtype, low=None, high=None, requires_grad=requires_grad),
)
),
)
def sample_inputs_addmv(op_info, device, dtype, requires_grad, **kwargs):
test_cases = (((S,), (S, M), (M,), 1, 1, False),
((S,), (S, M), (M,), 0.2, 0.6, False),
@ -3047,8 +3077,7 @@ op_db: List[OpInfo] = [
OpInfo('addbmm',
dtypes=floating_types(),
dtypesIfCPU=all_types_and_complex_and(torch.float16, torch.bfloat16),
dtypesIfCUDA=floating_types_and(torch.float16, torch.complex64, torch.complex128,
*[torch.bfloat16] if CUDA11OrLater else []),
dtypesIfCUDA=floating_and_complex_types_and(torch.float16, *[torch.bfloat16] if CUDA11OrLater else []),
dtypesIfROCM=floating_types_and(torch.half),
skips=(
# addbmm does not correctly warn when resizing out= inputs
@ -3061,6 +3090,50 @@ op_db: List[OpInfo] = [
SkipInfo('TestOpInfo', 'test_supported_backward', dtypes=(torch.bfloat16, ),
device_type='cuda', active_if=not SM53OrLater)),
sample_inputs_func=sample_inputs_addbmm),
OpInfo('dot',
dtypes=all_types_and_complex_and(torch.float16),
dtypesIfCUDA=floating_and_complex_types_and(torch.float16),
skips=(
# dot does not handle correctly out= dtypes
# https://github.com/pytorch/pytorch/issues/55561
SkipInfo('TestCommon', 'test_out'),
),
assert_autodiffed=True,
sample_inputs_func=sample_inputs_dot_vdot),
OpInfo('vdot',
dtypes=all_types_and_complex_and(torch.float16),
dtypesIfCUDA=floating_and_complex_types_and(torch.float16),
skips=(
# vdot does not handle correctly out= dtypes
# https://github.com/pytorch/pytorch/issues/55561
SkipInfo('TestCommon', 'test_out'),
),
sample_inputs_func=sample_inputs_dot_vdot),
OpInfo('bmm',
dtypes=all_types_and_complex_and(torch.bfloat16, torch.float16),
dtypesIfCUDA=floating_and_complex_types_and(torch.float16, *[torch.bfloat16] if CUDA11OrLater else []),
assert_autodiffed=True,
skips=(
# bmm does not correctly warn when resizing out= inputs
SkipInfo('TestCommon', 'test_out'),
# cuda gradchecks are slow
# see discussion https://github.com/pytorch/pytorch/pull/47761#issuecomment-747316775
SkipInfo('TestGradients', 'test_fn_gradgrad', device_type='cuda'),
SkipInfo('TestOpInfo', 'test_supported_backward', dtypes=(torch.bfloat16, ),
device_type='cuda', active_if=not SM53OrLater)),
sample_inputs_func=sample_inputs_bmm),
OpInfo('mv',
dtypes=all_types_and_complex_and(torch.float16, torch.bfloat16),
dtypesIfCUDA=floating_and_complex_types_and(torch.float16, *[torch.bfloat16] if CUDA11OrLater else []),
skips=(
# bmm does not correctly warn when resizing out= inputs
SkipInfo('TestCommon', 'test_out'),
SkipInfo('TestOpInfo', 'test_supported_backward', dtypes=(torch.float16,)),
# mv calls into addmv which doesn't fully support float16
# RuntimeError: "addmv_impl_cpu" not implemented for 'Half'
SkipInfo('TestOpInfo', 'test_supported_dtypes', dtypes=(torch.float16,)),),
assert_autodiffed=True,
sample_inputs_func=sample_inputs_mv),
OpInfo('addr',
dtypes=all_types_and_complex_and(torch.bool, torch.bfloat16, torch.float16),
# Reference: https://github.com/pytorch/pytorch/issues/50747
@ -5270,10 +5343,6 @@ def method_tests():
('baddbmm', (), ((S, S, S), (S, S, M)), 'scalar_broadcast_lhs'),
('baddbmm', (), ((S, S, S), (S, S, M)), 'scalar_broadcast_lhs_coef', (), (), (), ident,
{'beta': 0.2, 'alpha': 0.6}),
('dot', (L,), ((L,),), '', (True,)),
('vdot', (L,), ((L,),),),
('bmm', (M, S, M), ((M, M, S),), '', (True,)),
('mv', (S, M), ((M,),), '', (True,)),
('mvlgamma', torch.empty(S,).uniform_(0.5, 1), [1], "p=1"),
('mvlgamma', torch.empty(S,).uniform_(1, 2), [2], "p=2"),
('mvlgamma', torch.empty(S, S).uniform_(1.5, 3), [3], "p=3"),