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fix: update tests of pooling converters #2613

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merged 1 commit into from
Feb 15, 2024
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fix: update tests of pooling converters #2613

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113 changes: 44 additions & 69 deletions tests/py/dynamo/conversion/test_pool_aten.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,11 +10,11 @@ class TestPoolConverter(DispatchTestCase):
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
(2, None, 0),
(4, 1, 1),
(5, 2, 0),
(7, 2, 1),
((3,), (1,), (1,)),
((2,), [], (0,)),
((4,), (1,), (1,)),
((5,), (2,), (0,)),
((7,), (2,), (1,)),
]
)
def test_avg_pool1d(
Expand All @@ -26,14 +26,10 @@ def test_avg_pool1d(
count_include_pad=True,
):
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.pool = torch.nn.AvgPool1d(
kernel_size, stride, padding, ceil_mode, count_include_pad
)

def forward(self, x):
return self.pool(x)
return torch.ops.aten.avg_pool1d.default(
x, kernel_size, stride, padding, ceil_mode, count_include_pad
)

inputs = [torch.randn(1, 3, 32)]
self.run_test(
Expand All @@ -46,7 +42,7 @@ def forward(self, x):
[
(3, 1, 0),
(3, 1, 1),
((2, 2), None, (1, 0)),
((2, 2), [], (1, 0)),
((4, 3), (1, 1), (1, 1)),
((5, 4), (2, 1), (1, 0)),
((7, 7), (1, 2), (0, 1)),
Expand All @@ -62,9 +58,9 @@ def test_avg_pool2d(
divisor_override=None,
):
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.pool = torch.nn.AvgPool2d(
def forward(self, x):
return torch.ops.aten.avg_pool2d.default(
x,
kernel_size,
stride,
padding,
Expand All @@ -73,17 +69,14 @@ def __init__(self):
divisor_override,
)

def forward(self, x):
return self.pool(x)

inputs = [torch.randn(1, 3, 32, 32)]
self.run_test(TestModule(), inputs, use_dynamo_tracer=True)

@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
((2, 2, 3), None, (1, 0, 1)),
((2, 2, 3), [], (1, 0, 1)),
((4, 3, 2), (1, 1, 1), (1, 1, 0)),
((5, 4, 3), (2, 1, 2), (1, 0, 1)),
((7, 7, 7), (1, 2, 1), (0, 1, 1)),
Expand All @@ -99,9 +92,9 @@ def test_avg_pool3d(
divisor_override=None,
):
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.pool = torch.nn.AvgPool3d(
def forward(self, x):
return torch.ops.aten.avg_pool3d.default(
x,
kernel_size,
stride,
padding,
Expand All @@ -110,20 +103,17 @@ def __init__(self):
divisor_override,
)

def forward(self, x):
return self.pool(x)

inputs = [torch.randn(1, 3, 32, 32, 32)]
self.run_test(TestModule(), inputs, use_dynamo_tracer=True)

@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
(2, None, 0),
(4, 1, 1),
(5, 2, 0),
(7, 2, 1),
((3,), (1,), (1,)),
((2,), [], (0,)),
((4,), (1,), (1,)),
((5,), (2,), (0,)),
((7,), (2,), (1,)),
]
)
def test_max_pool1d(
Expand All @@ -132,18 +122,13 @@ def test_max_pool1d(
stride,
padding,
dilation=1,
return_indices=False,
ceil_mode=False,
):
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.pool = torch.nn.MaxPool1d(
kernel_size, stride, padding, dilation, return_indices, ceil_mode
)

def forward(self, x):
return self.pool(x)
return torch.ops.aten.max_pool1d.default(
x, kernel_size, stride, padding, dilation, ceil_mode
)

inputs = [torch.randn(1, 3, 32)]
self.run_test(
Expand All @@ -157,7 +142,7 @@ def forward(self, x):
[
(3, 1, 0),
(3, 1, 1),
((2, 2), None, (1, 0)),
((2, 2), [], (1, 0)),
((4, 3), (1, 1), (1, 1)),
((5, 4), (2, 1), (1, 0)),
((7, 7), (1, 2), (0, 1)),
Expand All @@ -169,32 +154,27 @@ def test_max_pool2d(
stride,
padding,
dilation=1,
return_indices=False,
ceil_mode=False,
):
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.pool = torch.nn.MaxPool2d(
kernel_size,
stride,
padding,
dilation,
return_indices,
ceil_mode,
)

def forward(self, x):
return self.pool(x)
return torch.ops.aten.max_pool2d.default(
x, kernel_size, stride, padding, dilation, ceil_mode
)

inputs = [torch.randn(1, 3, 32, 32)]
self.run_test(TestModule(), inputs, use_dynamo_tracer=True, enable_passes=True)
self.run_test(
TestModule(),
inputs,
use_dynamo_tracer=True,
enable_passes=True,
)

@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
((2, 2, 3), None, (1, 0, 1)),
((2, 2, 3), [], (1, 0, 1)),
((4, 3, 2), (1, 1, 1), (1, 1, 0)),
((5, 4, 3), (2, 1, 2), (1, 0, 1)),
((7, 7, 7), (1, 2, 1), (0, 1, 1)),
Expand All @@ -206,26 +186,21 @@ def test_max_pool3d(
stride,
padding,
dilation=1,
return_indices=False,
ceil_mode=False,
):
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.pool = torch.nn.MaxPool3d(
kernel_size,
stride,
padding,
dilation,
return_indices,
ceil_mode,
)

def forward(self, x):
return self.pool(x)
return torch.ops.aten.max_pool3d.default(
x, kernel_size, stride, padding, dilation, ceil_mode
)

inputs = [torch.randn(1, 3, 32, 32, 32)]
self.run_test(TestModule(), inputs, use_dynamo_tracer=True, enable_passes=True)
self.run_test(
TestModule(),
inputs,
use_dynamo_tracer=True,
enable_passes=True,
)


if __name__ == "__main__":
Expand Down