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[proto] Fixes Transform._transformed_types and torch.Tensor #6487

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Merged
merged 6 commits into from
Aug 25, 2022
Merged

[proto] Fixes Transform._transformed_types and torch.Tensor #6487

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eefa6fe
Fixes unexpected behaviour with Transform._transformed_types and torc…
vfdev-5 Aug 24, 2022
6788b45
Merge branch 'main' into proto-fix-transformed_types
vfdev-5 Aug 24, 2022
847a4a6
Make code consistent to has_any, has_all implementation
vfdev-5 Aug 25, 2022
8499e5d
Merge branch 'proto-fix-transformed_types' of github.com:vfdev-5/visi…
vfdev-5 Aug 25, 2022
db5fab3
Merge branch 'main' into proto-fix-transformed_types
vfdev-5 Aug 25, 2022
8766032
Fixed failing flake8 check
vfdev-5 Aug 25, 2022
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11 changes: 10 additions & 1 deletion test/test_prototype_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -225,9 +225,18 @@ def test_random_resized_crop(self, transform, input):
)
]
)
def test_convertolor_space(self, transform, input):
def test_convert_color_space(self, transform, input):
transform(input)

def test_convert_color_space_unsupported_types(self):
transform = transforms.ConvertColorSpace(
color_space=features.ColorSpace.RGB, old_color_space=features.ColorSpace.GRAY
)

for inpt in [make_bounding_box(format="XYXY"), make_segmentation_mask()]:
output = transform(inpt)
assert output is inpt


@pytest.mark.parametrize("p", [0.0, 1.0])
class TestRandomHorizontalFlip:
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12 changes: 11 additions & 1 deletion torchvision/prototype/transforms/_transform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,18 @@
from torch import nn
from torch.utils._pytree import tree_flatten, tree_unflatten
from torchvision.prototype.features import _Feature
from torchvision.prototype.transforms._utils import is_simple_tensor
from torchvision.utils import _log_api_usage_once


def _isinstance(obj: Any, types: Tuple[Type, ...]) -> bool:
has_tensor = torch.Tensor in types
if not has_tensor:
return isinstance(obj, types)
types_ = tuple(t for t in types if t != torch.Tensor)
return isinstance(obj, types_) or is_simple_tensor(obj)


class Transform(nn.Module):

# Class attribute defining transformed types. Other types are passed-through without any transformation
Expand All @@ -31,7 +40,8 @@ def forward(self, *inputs: Any) -> Any:

flat_inputs, spec = tree_flatten(sample)
flat_outputs = [
self._transform(inpt, params) if isinstance(inpt, self._transformed_types) else inpt for inpt in flat_inputs
self._transform(inpt, params) if _isinstance(inpt, self._transformed_types) else inpt
for inpt in flat_inputs
]
return tree_unflatten(flat_outputs, spec)

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