Remove _wrap() class method from base class Datapoint
#7805
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/vision/7805
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_wrap() class method from base class Datapoint
NicolasHug
commented
Aug 7, 2023
Comment on lines
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| def test_no_wrapping_exceptions_with_metadata(): | ||
| # Sanity checks for the ops in _NO_WRAPPING_EXCEPTIONS and datapoints with metadata |
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If you're wondering why I added this test, it's because I originally had changed the _NO_WRAPPING_EXCEPTIONS to return output.as_subclass(cls) instead of cls.wrap_like(input, output), and I didn't get a proper error in the tests. The only tests that were failing here were test_deepcopy() which was failing on print(bbox), which is a bit too "remote" of a test.
pmeier
approved these changes
Aug 7, 2023
| @@ -42,7 +42,9 @@ class BoundingBoxes(Datapoint): | |||
| canvas_size: Tuple[int, int] | |||
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| @classmethod | |||
| def _wrap(cls, tensor: torch.Tensor, *, format: BoundingBoxFormat, canvas_size: Tuple[int, int]) -> BoundingBoxes: # type: ignore[override] | |||
| def _wrap(cls, tensor: torch.Tensor, *, format: Union[BoundingBoxFormat, str], canvas_size: Tuple[int, int]) -> BoundingBoxes: # type: ignore[override] | |||
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Since Datapoint._wrap is removed now, do we still need the mypy directive?
Suggested change
| def _wrap(cls, tensor: torch.Tensor, *, format: Union[BoundingBoxFormat, str], canvas_size: Tuple[int, int]) -> BoundingBoxes: # type: ignore[override] | |
| def _wrap(cls, tensor: torch.Tensor, *, format: Union[BoundingBoxFormat, str], canvas_size: Tuple[int, int]) -> BoundingBoxes: |
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Reviewed By: matteobettini Differential Revision: D48642288 fbshipit-source-id: cce9803e2a4478afcbf56b052ff1ae39e1dc0b2d
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Towards #7803
This mostly just removes
_wrap()from the base class.Also minor cleanup of bbox code + some test.
cc @vfdev-5