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Port remaining transforms tests #7954

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merged 26 commits into from
Sep 26, 2023
Merged

Port remaining transforms tests #7954

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348231d
port tests for F.equalize and transforms.RandomEqualize
pmeier Sep 11, 2023
7882863
port tests for F.uniform_temporal_subsample and transforms.UniformTem…
pmeier Sep 11, 2023
9b5b7c4
port tests for F.normalize and transforms.Normalize
pmeier Sep 11, 2023
c69eb28
cleanup
pmeier Sep 11, 2023
0a6413a
port tests for F.clamp_bounding_boxes and transforms.ClampBoundingBoxes
pmeier Sep 11, 2023
227ca27
fix normalize tests
pmeier Sep 11, 2023
734d0b7
port tests for F.invert and transforms.RandomInvert
pmeier Sep 11, 2023
845ac36
add new tests for F.posterize and transforms.RandomPosterize
pmeier Sep 11, 2023
472ec15
add new tests for F.solarize and transforms.RandomSolarize
pmeier Sep 11, 2023
41cfdad
add new tests for F.autocontrast and transforms.RandomAutocontrast
pmeier Sep 11, 2023
40f21b2
add new tests for F.adjust_sharpness and transforms.RandomAdjustSharp…
pmeier Sep 11, 2023
635c2c4
add new tests for F.adjust_contrast
pmeier Sep 11, 2023
257d0f4
add new tests for F.adjust_gamma
pmeier Sep 11, 2023
c959590
add new tests for F.adjust_hue
pmeier Sep 11, 2023
8cd9fdf
add new tests for F.adjust_saturation
pmeier Sep 11, 2023
555d44a
cleanup
pmeier Sep 11, 2023
0683b1c
fix normalize
pmeier Sep 12, 2023
01992d3
add tests for five / ten crop
pmeier Sep 12, 2023
775e5ec
cleanup
pmeier Sep 13, 2023
a845f30
add normalize correctness test
pmeier Sep 26, 2023
bcc8710
localize five ten crop special cases
pmeier Sep 26, 2023
c2a60ae
Merge branch 'main' into port
pmeier Sep 26, 2023
bc9b68e
Merge branch 'main' into port
pmeier Sep 26, 2023
64737ba
fix solarize correctness
pmeier Sep 26, 2023
58d6ecb
fix five / ten crop
pmeier Sep 26, 2023
7902956
simplify equalize correctness
pmeier Sep 26, 2023
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104 changes: 0 additions & 104 deletions test/test_transforms_v2.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -272,57 +272,6 @@ def test_common(self, transform, adapter, container_type, image_or_video, de_ser
)
assert transforms.SanitizeBoundingBoxes()(sample)["boxes"].shape == (0, 4)

@parametrize(
[
(
transform,
itertools.chain.from_iterable(
fn(
color_spaces=[
"GRAY",
"RGB",
],
dtypes=[torch.uint8],
extra_dims=[(), (4,)],
**(dict(num_frames=[3]) if fn is make_videos else dict()),
)
for fn in [
make_images,
make_vanilla_tensor_images,
make_pil_images,
make_videos,
]
),
)
for transform in (
transforms.RandAugment(),
transforms.TrivialAugmentWide(),
transforms.AutoAugment(),
transforms.AugMix(),
)
]
)
def test_auto_augment(self, transform, input):
transform(input)

@parametrize(
[
(
transforms.Normalize(mean=[0.0, 0.0, 0.0], std=[1.0, 1.0, 1.0]),
itertools.chain.from_iterable(
fn(color_spaces=["RGB"], dtypes=[torch.float32])
for fn in [
make_images,
make_vanilla_tensor_images,
make_videos,
]
),
),
]
)
def test_normalize(self, transform, input):
transform(input)


@pytest.mark.parametrize(
"flat_inputs",
Expand Down Expand Up @@ -385,40 +334,6 @@ def was_applied(output, inpt):
assert transform.was_applied(output, input)


class TestElasticTransform:
def test_assertions(self):

with pytest.raises(TypeError, match="alpha should be a number or a sequence of numbers"):
transforms.ElasticTransform({})

with pytest.raises(ValueError, match="alpha is a sequence its length should be 1 or 2"):
transforms.ElasticTransform([1.0, 2.0, 3.0])

with pytest.raises(TypeError, match="sigma should be a number or a sequence of numbers"):
transforms.ElasticTransform(1.0, {})

with pytest.raises(ValueError, match="sigma is a sequence its length should be 1 or 2"):
transforms.ElasticTransform(1.0, [1.0, 2.0, 3.0])

with pytest.raises(TypeError, match="Got inappropriate fill arg"):
transforms.ElasticTransform(1.0, 2.0, fill="abc")

def test__get_params(self):
alpha = 2.0
sigma = 3.0
transform = transforms.ElasticTransform(alpha, sigma)

h, w = size = (24, 32)
image = make_image(size)

params = transform._get_params([image])

displacement = params["displacement"]
assert displacement.shape == (1, h, w, 2)
assert (-alpha / w <= displacement[0, ..., 0]).all() and (displacement[0, ..., 0] <= alpha / w).all()
assert (-alpha / h <= displacement[0, ..., 1]).all() and (displacement[0, ..., 1] <= alpha / h).all()


class TestTransform:
@pytest.mark.parametrize(
"inpt_type",
Expand Down Expand Up @@ -705,25 +620,6 @@ def test__get_params(self):
assert min_size <= size < max_size


class TestUniformTemporalSubsample:
@pytest.mark.parametrize(
"inpt",
[
torch.zeros(10, 3, 8, 8),
torch.zeros(1, 10, 3, 8, 8),
tv_tensors.Video(torch.zeros(1, 10, 3, 8, 8)),
],
)
def test__transform(self, inpt):
num_samples = 5
transform = transforms.UniformTemporalSubsample(num_samples)

output = transform(inpt)
assert type(output) is type(inpt)
assert output.shape[-4] == num_samples
assert output.dtype == inpt.dtype


@pytest.mark.parametrize("image_type", (PIL.Image, torch.Tensor, tv_tensors.Image))
@pytest.mark.parametrize("label_type", (torch.Tensor, int))
@pytest.mark.parametrize("dataset_return_type", (dict, tuple))
Expand Down
130 changes: 0 additions & 130 deletions test/test_transforms_v2_consistency.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -72,34 +72,6 @@ def __init__(
LINEAR_TRANSFORMATION_MATRIX = torch.rand([LINEAR_TRANSFORMATION_MEAN.numel()] * 2)

CONSISTENCY_CONFIGS = [
ConsistencyConfig(
v2_transforms.Normalize,
legacy_transforms.Normalize,
[
ArgsKwargs(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)),
],
supports_pil=False,
make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, dtypes=[torch.float]),
),
ConsistencyConfig(
v2_transforms.FiveCrop,
legacy_transforms.FiveCrop,
[
ArgsKwargs(18),
ArgsKwargs((18, 13)),
],
make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, sizes=[(20, 19)]),
),
ConsistencyConfig(
v2_transforms.TenCrop,
legacy_transforms.TenCrop,
[
ArgsKwargs(18),
ArgsKwargs((18, 13)),
ArgsKwargs(18, vertical_flip=True),
],
make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, sizes=[(20, 19)]),
),
*[
ConsistencyConfig(
v2_transforms.LinearTransformation,
Expand Down Expand Up @@ -147,65 +119,6 @@ def __init__(
# images given that the transform does nothing but call it anyway.
supports_pil=False,
),
ConsistencyConfig(
v2_transforms.RandomEqualize,
legacy_transforms.RandomEqualize,
[
ArgsKwargs(p=0),
ArgsKwargs(p=1),
],
make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, dtypes=[torch.uint8]),
),
ConsistencyConfig(
v2_transforms.RandomInvert,
legacy_transforms.RandomInvert,
[
ArgsKwargs(p=0),
ArgsKwargs(p=1),
],
),
ConsistencyConfig(
v2_transforms.RandomPosterize,
legacy_transforms.RandomPosterize,
[
ArgsKwargs(p=0, bits=5),
ArgsKwargs(p=1, bits=1),
ArgsKwargs(p=1, bits=3),
],
make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, dtypes=[torch.uint8]),
),
ConsistencyConfig(
v2_transforms.RandomSolarize,
legacy_transforms.RandomSolarize,
[
ArgsKwargs(p=0, threshold=0.5),
ArgsKwargs(p=1, threshold=0.3),
ArgsKwargs(p=1, threshold=0.99),
],
),
*[
ConsistencyConfig(
v2_transforms.RandomAutocontrast,
legacy_transforms.RandomAutocontrast,
[
ArgsKwargs(p=0),
ArgsKwargs(p=1),
],
make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, dtypes=[dt]),
closeness_kwargs=ckw,
)
for dt, ckw in [(torch.uint8, dict(atol=1, rtol=0)), (torch.float32, dict(rtol=None, atol=None))]
],
ConsistencyConfig(
v2_transforms.RandomAdjustSharpness,
legacy_transforms.RandomAdjustSharpness,
[
ArgsKwargs(p=0, sharpness_factor=0.5),
ArgsKwargs(p=1, sharpness_factor=0.2),
ArgsKwargs(p=1, sharpness_factor=0.99),
],
closeness_kwargs={"atol": 1e-6, "rtol": 1e-6},
),
ConsistencyConfig(
v2_transforms.PILToTensor,
legacy_transforms.PILToTensor,
Expand All @@ -230,22 +143,6 @@ def __init__(
v2_transforms.RandomOrder,
legacy_transforms.RandomOrder,
),
ConsistencyConfig(
v2_transforms.AugMix,
legacy_transforms.AugMix,
),
ConsistencyConfig(
v2_transforms.AutoAugment,
legacy_transforms.AutoAugment,
),
ConsistencyConfig(
v2_transforms.RandAugment,
legacy_transforms.RandAugment,
),
ConsistencyConfig(
v2_transforms.TrivialAugmentWide,
legacy_transforms.TrivialAugmentWide,
),
]


Expand Down Expand Up @@ -753,36 +650,9 @@ def test_common(self, t_ref, t, data_kwargs):
(legacy_F.pil_to_tensor, {}),
(legacy_F.convert_image_dtype, {}),
(legacy_F.to_pil_image, {}),
(legacy_F.normalize, {}),
(legacy_F.resize, {"interpolation"}),
(legacy_F.pad, {"padding", "fill"}),
(legacy_F.crop, {}),
(legacy_F.center_crop, {}),
(legacy_F.resized_crop, {"interpolation"}),
(legacy_F.hflip, {}),
(legacy_F.perspective, {"startpoints", "endpoints", "fill", "interpolation"}),
(legacy_F.vflip, {}),
(legacy_F.five_crop, {}),
(legacy_F.ten_crop, {}),
(legacy_F.adjust_brightness, {}),
(legacy_F.adjust_contrast, {}),
(legacy_F.adjust_saturation, {}),
(legacy_F.adjust_hue, {}),
(legacy_F.adjust_gamma, {}),
(legacy_F.rotate, {"center", "fill", "interpolation"}),
(legacy_F.affine, {"angle", "translate", "center", "fill", "interpolation"}),
(legacy_F.to_grayscale, {}),
(legacy_F.rgb_to_grayscale, {}),
(legacy_F.to_tensor, {}),
(legacy_F.erase, {}),
(legacy_F.gaussian_blur, {}),
(legacy_F.invert, {}),
(legacy_F.posterize, {}),
(legacy_F.solarize, {}),
(legacy_F.adjust_sharpness, {}),
(legacy_F.autocontrast, {}),
(legacy_F.equalize, {}),
(legacy_F.elastic_transform, {"fill", "interpolation"}),
],
)
def test_dispatcher_signature_consistency(legacy_dispatcher, name_only_params):
Expand Down
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