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Jun 24, 2024
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add dynamic shape support for amax/amin/max/min/prod/sum #2943

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32 changes: 21 additions & 11 deletions py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1085,7 +1085,7 @@ def aten_ops_expand(
)


@dynamo_tensorrt_converter(torch.ops.aten.amax.default)
@dynamo_tensorrt_converter(torch.ops.aten.amax.default, supports_dynamic_shapes=True)
@enforce_tensor_types(
{
0: (TRTTensor,),
Expand All @@ -1109,7 +1109,7 @@ def aten_ops_amax(
)


@dynamo_tensorrt_converter(torch.ops.aten.amin.default)
@dynamo_tensorrt_converter(torch.ops.aten.amin.default, supports_dynamic_shapes=True)
@enforce_tensor_types(
{
0: (TRTTensor,),
Expand All @@ -1133,9 +1133,9 @@ def aten_ops_amin(
)


@dynamo_tensorrt_converter(torch.ops.aten.sum.default)
@dynamo_tensorrt_converter(torch.ops.aten.sum.dim_IntList)
@dynamo_tensorrt_converter(torch.ops.prims.sum.default)
@dynamo_tensorrt_converter(torch.ops.aten.sum.default, supports_dynamic_shapes=True)
@dynamo_tensorrt_converter(torch.ops.aten.sum.dim_IntList, supports_dynamic_shapes=True)
@dynamo_tensorrt_converter(torch.ops.prims.sum.default, supports_dynamic_shapes=True)
def aten_ops_sum(
ctx: ConversionContext,
target: Target,
Expand Down Expand Up @@ -1167,8 +1167,8 @@ def aten_ops_sum(
return sum_


@dynamo_tensorrt_converter(torch.ops.aten.prod.default)
@dynamo_tensorrt_converter(torch.ops.aten.prod.dim_int)
@dynamo_tensorrt_converter(torch.ops.aten.prod.default, supports_dynamic_shapes=True)
@dynamo_tensorrt_converter(torch.ops.aten.prod.dim_int, supports_dynamic_shapes=True)
def aten_ops_prod(
ctx: ConversionContext,
target: Target,
Expand All @@ -1187,9 +1187,14 @@ def aten_ops_prod(
)


@dynamo_tensorrt_converter(torch.ops.aten.max.default)
@dynamo_tensorrt_converter(
torch.ops.aten.max.dim, capability_validator=one_user_validator
torch.ops.aten.max.default,
supports_dynamic_shapes=True,
)
@dynamo_tensorrt_converter(
torch.ops.aten.max.dim,
capability_validator=one_user_validator,
supports_dynamic_shapes=True,
)
def aten_ops_max(
ctx: ConversionContext,
Expand All @@ -1210,9 +1215,14 @@ def aten_ops_max(
)


@dynamo_tensorrt_converter(torch.ops.aten.min.default)
@dynamo_tensorrt_converter(
torch.ops.aten.min.dim, capability_validator=one_user_validator
torch.ops.aten.min.default,
supports_dynamic_shapes=True,
)
@dynamo_tensorrt_converter(
torch.ops.aten.min.dim,
capability_validator=one_user_validator,
supports_dynamic_shapes=True,
)
def aten_ops_min(
ctx: ConversionContext,
Expand Down
33 changes: 33 additions & 0 deletions tests/py/dynamo/conversion/test_amax_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import torch.nn as nn
from parameterized import parameterized
from torch.testing._internal.common_utils import run_tests
from torch_tensorrt import Input

from .harness import DispatchTestCase

Expand Down Expand Up @@ -90,6 +91,38 @@ def forward(self, x):
check_dtype=False,
)

@parameterized.expand(
[
((0, 1), True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
((0,), True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(1, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(2, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(-1, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
((-1, 0), True, (2, 2, 5), (3, 3, 6), (4, 5, 7)),
]
)
def test_amax_dynamic_shape(self, dim, keep_dim, min_shape, opt_shape, max_shape):
class Amax(nn.Module):
def __init__(self, dim):
super().__init__()
self.dim = dim

def forward(self, x):
return torch.ops.aten.amax.default(x, dim, keep_dim)

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Amax(dim),
input_specs,
)


if __name__ == "__main__":
run_tests()
33 changes: 33 additions & 0 deletions tests/py/dynamo/conversion/test_amin_aten.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import torch.nn as nn
from parameterized import parameterized
from torch.testing._internal.common_utils import run_tests
from torch_tensorrt import Input

from .harness import DispatchTestCase

Expand Down Expand Up @@ -90,6 +91,38 @@ def forward(self, x):
check_dtype=False,
)

@parameterized.expand(
[
((0, 1), True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
((0,), False, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(1, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(2, False, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(-1, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
((-1, 0), True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
]
)
def test_amin_dynamic_shape(self, dim, keep_dim, min_shape, opt_shape, max_shape):
class Amin(nn.Module):
def __init__(self, dim):
super().__init__()
self.dim = dim

def forward(self, x):
return torch.ops.aten.amin.default(x, dim, keep_dim)

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Amin(dim),
input_specs,
)


if __name__ == "__main__":
run_tests()
57 changes: 57 additions & 0 deletions tests/py/dynamo/conversion/test_max_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import torch.nn as nn
from parameterized import parameterized
from torch.testing._internal.common_utils import run_tests
from torch_tensorrt import Input

from .harness import DispatchTestCase

Expand Down Expand Up @@ -65,6 +66,62 @@ def forward(self, x):
check_dtype=False,
)

@parameterized.expand(
[
(1, True, (2, 2, 3), (2, 3, 3), (3, 3, 4)),
(2, False, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(-1, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
]
)
def test_max_dim_dynamic_shape(
self, dim, keep_dim, min_shape, opt_shape, max_shape
):
class Max(nn.Module):
def __init__(self, dim):
super().__init__()
self.dim = dim

def forward(self, x):
return torch.ops.aten.max.dim(x, dim, keep_dim)[0]

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Max(dim),
input_specs,
)

@parameterized.expand(
[
((2, 2, 3), (2, 3, 3), (3, 3, 4)),
((2, 3, 5), (3, 4, 6), (4, 5, 7)),
((2, 3, 5), (3, 4, 6), (4, 5, 7)),
]
)
def test_max_default_dynamic_shape(self, min_shape, opt_shape, max_shape):
class Max(nn.Module):
def forward(self, x):
return torch.ops.aten.max.default(x)

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Max(),
input_specs,
)


if __name__ == "__main__":
run_tests()
57 changes: 57 additions & 0 deletions tests/py/dynamo/conversion/test_min_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import torch.nn as nn
from parameterized import parameterized
from torch.testing._internal.common_utils import run_tests
from torch_tensorrt import Input

from .harness import DispatchTestCase

Expand Down Expand Up @@ -65,6 +66,62 @@ def forward(self, x):
check_dtype=False,
)

@parameterized.expand(
[
(1, True, (2, 2, 3), (2, 3, 3), (3, 3, 4)),
(2, False, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
(-1, True, (2, 3, 5), (3, 4, 6), (4, 5, 7)),
]
)
def test_min_dim_dynamic_shape(
self, dim, keep_dim, min_shape, opt_shape, max_shape
):
class Min(nn.Module):
def __init__(self, dim):
super().__init__()
self.dim = dim

def forward(self, x):
return torch.ops.aten.min.dim(x, dim, keep_dim)[0]

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Min(dim),
input_specs,
)

@parameterized.expand(
[
((2, 2, 3), (2, 3, 3), (3, 3, 4)),
((2, 3, 5), (3, 4, 6), (4, 5, 7)),
((2, 3, 5), (3, 4, 6), (4, 5, 7)),
]
)
def test_min_default_dynamic_shape(self, min_shape, opt_shape, max_shape):
class Min(nn.Module):
def forward(self, x):
return torch.ops.aten.min.default(x)

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Min(),
input_specs,
)


if __name__ == "__main__":
run_tests()
28 changes: 28 additions & 0 deletions tests/py/dynamo/conversion/test_prod_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
import torch.nn as nn
from parameterized import parameterized
from torch.testing._internal.common_utils import run_tests
from torch_tensorrt import Input

from .harness import DispatchTestCase

Expand Down Expand Up @@ -68,6 +69,33 @@ def forward(self, x):
use_dynamo_tracer=True,
)

@parameterized.expand(
[
(0, (2, 3), (2, 4), (3, 5)),
(1, (2, 3), (2, 4), (3, 5)),
(2, (2, 2, 4), (2, 3, 4), (3, 4, 5)),
(-1, (2, 2, 4), (2, 3, 4), (3, 4, 5)),
]
)
def test_prod_dynamic_shape(self, dim, min_shape, opt_shape, max_shape):
class Prod(nn.Module):
def forward(self, x):
return torch.prod(x, dim)

input_specs = [
Input(
dtype=torch.float32,
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
),
]
self.run_test_with_dynamic_shape(
Prod(),
input_specs,
use_dynamo_tracer=True,
)


if __name__ == "__main__":
run_tests()
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