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chore: dynamic shape support for clamp/min/max/floor_div/logical_and #2977

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Merged
merged 4 commits into from
Jul 9, 2024
Merged

chore: dynamic shape support for clamp/min/max/floor_div/logical_and #2977

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86cf5d4
chore: dynamic shape support for clamp/maximum/minimum/floor_div/logi…
keehyuna Jul 2, 2024
042d1e5
chore: Update dynamic_partitioning test
keehyuna Jul 2, 2024
6e54ca9
chore: Add operator.floordiv
keehyuna Jul 8, 2024
70aa9ea
chore: Remove dynamic_partitioning test
keehyuna Jul 9, 2024
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25 changes: 16 additions & 9 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 @@ -733,10 +733,10 @@ def aten_ops_where(
)


@dynamo_tensorrt_converter(torch.ops.aten.clamp.default)
@dynamo_tensorrt_converter(torch.ops.aten.clamp.Tensor)
@dynamo_tensorrt_converter(torch.ops.aten.clip.default)
@dynamo_tensorrt_converter(torch.ops.aten.clip.Tensor)
@dynamo_tensorrt_converter(torch.ops.aten.clamp.default, supports_dynamic_shapes=True)
@dynamo_tensorrt_converter(torch.ops.aten.clamp.Tensor, supports_dynamic_shapes=True)
@dynamo_tensorrt_converter(torch.ops.aten.clip.default, supports_dynamic_shapes=True)
@dynamo_tensorrt_converter(torch.ops.aten.clip.Tensor, supports_dynamic_shapes=True)
def aten_ops_clamp(
ctx: ConversionContext,
target: Target,
Expand Down Expand Up @@ -1878,7 +1878,7 @@ def aten_ops_mul(
)


@dynamo_tensorrt_converter(torch.ops.aten.maximum.default)
@dynamo_tensorrt_converter(torch.ops.aten.maximum.default, supports_dynamic_shapes=True)
def aten_ops_maximum(
ctx: ConversionContext,
target: Target,
Expand All @@ -1896,7 +1896,7 @@ def aten_ops_maximum(
)


@dynamo_tensorrt_converter(torch.ops.aten.minimum.default)
@dynamo_tensorrt_converter(torch.ops.aten.minimum.default, supports_dynamic_shapes=True)
def aten_ops_minimum(
ctx: ConversionContext,
target: Target,
Expand Down Expand Up @@ -2017,8 +2017,13 @@ def aten_ops_pow(
)


@dynamo_tensorrt_converter(torch.ops.aten.floor_divide.default)
@dynamo_tensorrt_converter(torch.ops.aten.floor_divide.Scalar)
@dynamo_tensorrt_converter(
torch.ops.aten.floor_divide.default, supports_dynamic_shapes=True
)
@dynamo_tensorrt_converter(
torch.ops.aten.floor_divide.Scalar, supports_dynamic_shapes=True
)
@dynamo_tensorrt_converter(operator.floordiv, supports_dynamic_shapes=True)
def aten_ops_floor_div(
ctx: ConversionContext,
target: Target,
Expand All @@ -2036,7 +2041,9 @@ def aten_ops_floor_div(
)


@dynamo_tensorrt_converter(torch.ops.aten.logical_and.default)
@dynamo_tensorrt_converter(
torch.ops.aten.logical_and.default, supports_dynamic_shapes=True
)
def aten_ops_logical_and(
ctx: ConversionContext,
target: Target,
Expand Down
8 changes: 4 additions & 4 deletions tests/py/dynamo/conversion/test_clamp_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,12 +54,12 @@ def forward(self, x):

input_specs = [
Input(
shape=(-1, -1, 3, 3),
dtype=torch.float32,
shape_ranges=[((1, 1, 3, 3), (3, 3, 3, 3), (5, 5, 3, 3))],
min_shape=(1, 1, 3, 3),
opt_shape=(3, 3, 3, 3),
max_shape=(5, 5, 3, 3),
dtype=torch.float,
),
]

self.run_test_with_dynamic_shape(TestModule(), input_specs)
self.run_test_with_dynamic_shape(TestScalarModule(), input_specs)

Expand Down
52 changes: 52 additions & 0 deletions tests/py/dynamo/conversion/test_floor_div_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,6 +61,58 @@ def forward(self, lhs_val):
inputs,
)

@parameterized.expand(
[
(
"2d_dim_dtype_half",
(1, 1),
(2, 2),
(4, 4),
torch.half,
torch.half,
),
(
"3d_dim_dtype_float",
(1, 1, 1),
(1, 2, 3),
(3, 3, 3),
torch.float,
torch.float,
),
]
)
def test_floor_div_dynamic_shape(
self, _, min_shape, opt_shape, max_shape, type, output_type
):
class floor_div(nn.Module):
def forward(self, lhs_val, rhs_val):
return torch.ops.aten.floor_divide.default(lhs_val, rhs_val)

class floor_div_operator(nn.Module):
def forward(self, lhs_val, rhs_val):
return lhs_val // rhs_val

input_specs = [
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
]
self.run_test_with_dynamic_shape(
floor_div(), input_specs, output_dtypes=[output_type]
)
self.run_test_with_dynamic_shape(
floor_div_operator(), input_specs, output_dtypes=[output_type]
)


if __name__ == "__main__":
run_tests()
39 changes: 39 additions & 0 deletions tests/py/dynamo/conversion/test_logical_and_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,45 @@ def forward(self, lhs_val, rhs_val):
inputs,
)

@parameterized.expand(
[
(
"2d_dim_dtype_float",
(1, 1),
(2, 2),
(4, 4),
torch.float,
),
(
"3d_dim_dtype_bool",
(1, 1, 1),
(1, 2, 3),
(3, 3, 3),
torch.bool,
),
]
)
def test_logical_and_dynamic_shape(self, _, min_shape, opt_shape, max_shape, type):
class logical_and(nn.Module):
def forward(self, lhs_val, rhs_val):
return torch.ops.aten.logical_and.default(lhs_val, rhs_val)

input_specs = [
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
]
self.run_test_with_dynamic_shape(logical_and(), input_specs)


if __name__ == "__main__":
run_tests()
47 changes: 46 additions & 1 deletion tests/py/dynamo/conversion/test_maximum_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ class TestMaximumConverter(DispatchTestCase):
def test_maximum(self, _, shape):
class Maximum(nn.Module):
def forward(self, lhs_val, rhs_val):
return torch.maximum(lhs_val, rhs_val)
return torch.ops.aten.maximum.default(lhs_val, rhs_val)

inputs = [torch.randn(shape), torch.randn(shape)]
self.run_test(
Expand All @@ -26,6 +26,51 @@ def forward(self, lhs_val, rhs_val):
use_dynamo_tracer=True,
)

@parameterized.expand(
[
(
"2d_dim_dtype_half",
(1, 1),
(2, 2),
(4, 4),
torch.half,
torch.half,
),
(
"3d_dim_dtype_float",
(1, 1, 1),
(1, 2, 3),
(3, 3, 3),
torch.float,
torch.float,
),
]
)
def test_maximum_dynamic_shape(
self, _, min_shape, opt_shape, max_shape, type, output_type
):
class Maximum(nn.Module):
def forward(self, lhs_val, rhs_val):
return torch.ops.aten.maximum.default(lhs_val, rhs_val)

input_specs = [
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
]
self.run_test_with_dynamic_shape(
Maximum(), input_specs, output_dtypes=[output_type]
)


if __name__ == "__main__":
run_tests()
47 changes: 46 additions & 1 deletion tests/py/dynamo/conversion/test_minimum_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ class TestMinimumConverter(DispatchTestCase):
def test_minimum(self, _, shape):
class Minimum(nn.Module):
def forward(self, lhs_val, rhs_val):
return torch.minimum(lhs_val, rhs_val)
return torch.ops.aten.minimum.default(lhs_val, rhs_val)

inputs = [torch.randn(shape), torch.randn(shape)]
self.run_test(
Expand All @@ -26,6 +26,51 @@ def forward(self, lhs_val, rhs_val):
use_dynamo_tracer=True,
)

@parameterized.expand(
[
(
"2d_dim_dtype_half",
(1, 1),
(2, 2),
(4, 4),
torch.half,
torch.half,
),
(
"3d_dim_dtype_float",
(1, 1, 1),
(1, 2, 3),
(3, 3, 3),
torch.float,
torch.float,
),
]
)
def test_minimum_dynamic_shape(
self, _, min_shape, opt_shape, max_shape, type, output_type
):
class Minimum(nn.Module):
def forward(self, lhs_val, rhs_val):
return torch.ops.aten.minimum.default(lhs_val, rhs_val)

input_specs = [
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
Input(
min_shape=min_shape,
opt_shape=opt_shape,
max_shape=max_shape,
dtype=type,
),
]
self.run_test_with_dynamic_shape(
Minimum(), input_specs, output_dtypes=[output_type]
)


if __name__ == "__main__":
run_tests()
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