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Merged
merged 5 commits into from
May 16, 2022
Merged

Deprecate int as interpolation argument type #5974

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aa7487b
Requested here https://github.com/pytorch/vision/pull/5898#discussion…
kylematoba May 9, 2022
78ec780
Fix tests
kylematoba May 9, 2022
57b2227
ufmt, not black
kylematoba May 9, 2022
2d6cc02
Merge branch 'main' into main
pmeier May 16, 2022
0cd57d2
Merge branch 'main' into main
datumbox May 16, 2022
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32 changes: 28 additions & 4 deletions test/test_functional_tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,7 +156,13 @@ def test_rotate_deprecation_resample(self):
def test_rotate_interpolation_type(self):
tensor, _ = _create_data(26, 26)
# assert changed type warning
with pytest.warns(UserWarning, match=r"Argument interpolation should be of type InterpolationMode"):
with pytest.warns(
UserWarning,
match=re.escape(
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
),
):
res1 = F.rotate(tensor, 45, interpolation=2)
res2 = F.rotate(tensor, 45, interpolation=BILINEAR)
assert_equal(res1, res2)
Expand Down Expand Up @@ -384,7 +390,13 @@ def test_warnings(self, device):
assert_equal(res1, res2)

# assert changed type warning
with pytest.warns(UserWarning, match=r"Argument interpolation should be of type InterpolationMode"):
with pytest.warns(
UserWarning,
match=re.escape(
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
),
):
res1 = F.affine(tensor, 45, translate=[0, 0], scale=1.0, shear=[0.0, 0.0], interpolation=2)
res2 = F.affine(tensor, 45, translate=[0, 0], scale=1.0, shear=[0.0, 0.0], interpolation=BILINEAR)
assert_equal(res1, res2)
Expand Down Expand Up @@ -504,7 +516,13 @@ def test_perspective_interpolation_warning():
spoints = [[0, 0], [33, 0], [33, 25], [0, 25]]
epoints = [[3, 2], [32, 3], [30, 24], [2, 25]]
tensor = torch.randint(0, 256, (3, 26, 26))
with pytest.warns(UserWarning, match="Argument interpolation should be of type InterpolationMode"):
with pytest.warns(
UserWarning,
match=re.escape(
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
),
):
res1 = F.perspective(tensor, startpoints=spoints, endpoints=epoints, interpolation=2)
res2 = F.perspective(tensor, startpoints=spoints, endpoints=epoints, interpolation=BILINEAR)
assert_equal(res1, res2)
Expand Down Expand Up @@ -584,7 +602,13 @@ def test_resize_asserts(device):
tensor, pil_img = _create_data(26, 36, device=device)

# assert changed type warning
with pytest.warns(UserWarning, match=r"Argument interpolation should be of type InterpolationMode"):
with pytest.warns(
UserWarning,
match=re.escape(
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
),
):
res1 = F.resize(tensor, size=32, interpolation=2)

res2 = F.resize(tensor, size=32, interpolation=BILINEAR)
Expand Down
16 changes: 14 additions & 2 deletions test/test_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1878,7 +1878,13 @@ def test_random_rotation():
assert t.interpolation == transforms.InterpolationMode.BILINEAR

# assert changed type warning
with pytest.warns(UserWarning, match=r"Argument interpolation should be of type InterpolationMode"):
with pytest.warns(
UserWarning,
match=re.escape(
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
),
):
t = transforms.RandomRotation((-10, 10), interpolation=2)
assert t.interpolation == transforms.InterpolationMode.BILINEAR

Expand Down Expand Up @@ -2233,7 +2239,13 @@ def test_random_affine():
assert t.fill == 10

# assert changed type warning
with pytest.warns(UserWarning, match=r"Argument interpolation should be of type InterpolationMode"):
with pytest.warns(
UserWarning,
match=re.escape(
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
),
):
t = transforms.RandomAffine(10, interpolation=2)
assert t.interpolation == transforms.InterpolationMode.BILINEAR

Expand Down
32 changes: 18 additions & 14 deletions torchvision/transforms/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -392,7 +392,8 @@ def resize(
:class:`torchvision.transforms.InterpolationMode`.
Default is ``InterpolationMode.BILINEAR``. If input is Tensor, only ``InterpolationMode.NEAREST``,
``InterpolationMode.BILINEAR`` and ``InterpolationMode.BICUBIC`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
max_size (int, optional): The maximum allowed for the longer edge of
the resized image: if the longer edge of the image is greater
than ``max_size`` after being resized according to ``size``, then
Expand All @@ -414,8 +415,8 @@ def resize(
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -572,8 +573,8 @@ def resized_crop(
:class:`torchvision.transforms.InterpolationMode`.
Default is ``InterpolationMode.BILINEAR``. If input is Tensor, only ``InterpolationMode.NEAREST``,
``InterpolationMode.BILINEAR`` and ``InterpolationMode.BICUBIC`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.

For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
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@datumbox datumbox May 16, 2022 •
edited
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I would be in favour of removing from the documentation the deprecation notes and leave them only as warnings. This will help us keep clean our docs and promote the best practices/options. I would leave the warnings as-is to inform those who already use it to change.

What I describe above is exactly what we currently do for Multi-weight API. The documentation no longer mentions anything about pretrained. Only about weights.

@NicolasHug thoughts?

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@NicolasHug NicolasHug May 16, 2022 •
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The pretrained case is a bit special because we actually removed it plainly, while keeping BC as much as possible. But in general I'm in favour of documenting deprecations in the docstrings as well

Returns:
PIL Image or Tensor: Cropped image.
"""
Expand Down Expand Up @@ -652,7 +653,8 @@ def perspective(
interpolation (InterpolationMode): Desired interpolation enum defined by
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.BILINEAR``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
fill (sequence or number, optional): Pixel fill value for the area outside the transformed
image. If given a number, the value is used for all bands respectively.

Expand All @@ -671,8 +673,8 @@ def perspective(
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -1012,7 +1014,8 @@ def rotate(
interpolation (InterpolationMode): Desired interpolation enum defined by
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
expand (bool, optional): Optional expansion flag.
If true, expands the output image to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the input image.
Expand Down Expand Up @@ -1048,8 +1051,8 @@ def rotate(
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -1105,7 +1108,8 @@ def affine(
interpolation (InterpolationMode): Desired interpolation enum defined by
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
fill (sequence or number, optional): Pixel fill value for the area outside the transformed
image. If given a number, the value is used for all bands respectively.

Expand Down Expand Up @@ -1137,8 +1141,8 @@ def affine(
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down
40 changes: 21 additions & 19 deletions torchvision/transforms/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -297,7 +297,8 @@ class Resize(torch.nn.Module):
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.BILINEAR``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` and
``InterpolationMode.BICUBIC`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
max_size (int, optional): The maximum allowed for the longer edge of
the resized image: if the longer edge of the image is greater
than ``max_size`` after being resized according to ``size``, then
Expand Down Expand Up @@ -329,8 +330,8 @@ def __init__(self, size, interpolation=InterpolationMode.BILINEAR, max_size=None
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -754,7 +755,8 @@ class RandomPerspective(torch.nn.Module):
interpolation (InterpolationMode): Desired interpolation enum defined by
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.BILINEAR``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
fill (sequence or number): Pixel fill value for the area outside the transformed
image. Default is ``0``. If given a number, the value is used for all bands respectively.
"""
Expand All @@ -767,8 +769,8 @@ def __init__(self, distortion_scale=0.5, p=0.5, interpolation=InterpolationMode.
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -868,8 +870,8 @@ class RandomResizedCrop(torch.nn.Module):
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.BILINEAR``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` and
``InterpolationMode.BICUBIC`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.

For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
"""

def __init__(self, size, scale=(0.08, 1.0), ratio=(3.0 / 4.0, 4.0 / 3.0), interpolation=InterpolationMode.BILINEAR):
Expand All @@ -887,8 +889,8 @@ def __init__(self, size, scale=(0.08, 1.0), ratio=(3.0 / 4.0, 4.0 / 3.0), interp
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -1267,7 +1269,8 @@ class RandomRotation(torch.nn.Module):
interpolation (InterpolationMode): Desired interpolation enum defined by
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
expand (bool, optional): Optional expansion flag.
If true, expands the output to make it large enough to hold the entire rotated image.
If false or omitted, make the output image the same size as the input image.
Expand Down Expand Up @@ -1300,8 +1303,8 @@ def __init__(
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -1388,7 +1391,8 @@ class RandomAffine(torch.nn.Module):
interpolation (InterpolationMode): Desired interpolation enum defined by
:class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``.
If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still acceptable.
For backward compatibility integer values (e.g. ``PIL.Image[.Resampling].NEAREST``) are still accepted,
but deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
fill (sequence or number): Pixel fill value for the area outside the transformed
image. Default is ``0``. If given a number, the value is used for all bands respectively.
fillcolor (sequence or number, optional):
Expand Down Expand Up @@ -1429,8 +1433,8 @@ def __init__(
# Backward compatibility with integer value
if isinstance(interpolation, int):
warnings.warn(
"Argument interpolation should be of type InterpolationMode instead of int. "
"Please, use InterpolationMode enum."
"Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. "
"Please use InterpolationMode enum."
)
interpolation = _interpolation_modes_from_int(interpolation)

Expand Down Expand Up @@ -1727,9 +1731,7 @@ def forward(self, img):

# cast self.value to script acceptable type
if isinstance(self.value, (int, float)):
value = [
self.value,
]
value = [self.value]
elif isinstance(self.value, str):
value = None
elif isinstance(self.value, tuple):
Expand Down